{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:30:06.859756451Z",
     "start_time": "2023-08-22T14:30:05.353850443Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import pywt\n",
    "\n",
    "import MyEDFImports as m\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import neurokit2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/CN223100.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/CP229110.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/CX230050.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/DG220020.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/DO223050.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/MyEDFImports.py:42: RuntimeWarning: Channel names are not unique, found duplicates for: {'CHIN EMG'}. Applying running numbers for duplicates.\n",
      "  raw = mne.io.read_raw_edf(path + \"//\" + name)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/LA216100.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/LM230010.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/TK221110.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/VC209100.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/VP214110.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n",
      "Extracting EDF parameters from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/WD224010.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/MyEDFImports.py:42: RuntimeWarning: Channel names are not unique, found duplicates for: {'CHIN EMG'}. Applying running numbers for duplicates.\n",
      "  raw = mne.io.read_raw_edf(path + \"//\" + name)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<RawEDF | CN223100.edf, 1 x 15611000 (31222.0 s), ~6 kB, data not loaded> with 1561 windows\n",
      "<RawEDF | CP229110.edf, 1 x 20078000 (40156.0 s), ~6 kB, data not loaded> with 2007 windows\n",
      "importing inverted file: CP229110.edf\n",
      "/home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/CP229110.edf\n",
      "<RawEDF | CX230050.edf, 1 x 17981000 (35962.0 s), ~6 kB, data not loaded> with 1798 windows\n",
      "<RawEDF | DG220020.edf, 1 x 17756000 (35512.0 s), ~6 kB, data not loaded> with 1775 windows\n",
      "<RawEDF | DO223050.edf, 1 x 18066500 (36133.0 s), ~6 kB, data not loaded> with 1806 windows\n",
      "<RawEDF | LA216100.edf, 1 x 16333500 (32667.0 s), ~6 kB, data not loaded> with 1633 windows\n",
      "<RawEDF | LM230010.edf, 1 x 17246500 (34493.0 s), ~6 kB, data not loaded> with 1724 windows\n",
      "<RawEDF | TK221110.edf, 1 x 15991000 (31982.0 s), ~6 kB, data not loaded> with 1599 windows\n",
      "<RawEDF | VC209100.edf, 1 x 18434500 (36869.0 s), ~6 kB, data not loaded> with 1843 windows\n",
      "<RawEDF | VP214110.edf, 1 x 17252500 (34505.0 s), ~6 kB, data not loaded> with 1725 windows\n",
      "<RawEDF | WD224010.edf, 1 x 17774000 (35548.0 s), ~6 kB, data not loaded> with 1777 windows\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//CN223100.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//CP229110.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//CX230050.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//DG220020.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//DO223050.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//LA216100.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//LM230010.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//TK221110.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//VC209100.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//VP214110.edf_stages.txt\n",
      "loading from /home/tadeusz/Desktop/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers//WD224010.edf_stages.txt\n"
     ]
    },
    {
     "data": {
      "text/plain": "(19248, 10000)"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = m.load_all_data()\n",
    "labels = m.load_all_labels()\n",
    "data.shape"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:30:15.735005840Z",
     "start_time": "2023-08-22T14:30:06.860226207Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [],
   "source": [
    "def plot_with_peaks(y, r_peaks, detector_name='nodetect', sampling_freq=500):\n",
    "    # convert sample to nr to time\n",
    "    r_ts = np.array(r_peaks) / sampling_freq\n",
    "    # plotting\n",
    "    plt.figure()\n",
    "    t = np.linspace(0, len(y) / sampling_freq, len(y))\n",
    "    plt.plot(t, y)\n",
    "    plt.plot(r_ts, y[r_peaks], 'ro')\n",
    "    plt.title(f\"{detector_name}\")\n",
    "    plt.ylabel(\"ECG/mV\")\n",
    "    plt.xlabel(\"time/sec\")\n",
    "    plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:30:15.735379434Z",
     "start_time": "2023-08-22T14:30:15.726092773Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [],
   "source": [
    "def remove_from_data(data, mask):\n",
    "    assert len(data) == len(mask)\n",
    "    if type(data) == np.ndarray:\n",
    "        mask = np.array(mask)\n",
    "        return data[mask]\n",
    "    if type(data) == list:\n",
    "        return [a for a, b in zip(data, mask) if b == True]\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:30:15.735643647Z",
     "start_time": "2023-08-22T14:30:15.734485093Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [],
   "source": [
    "def make_wide_windows(datapoints,labels, win_pad=1):\n",
    "    labels = labels[win_pad:-win_pad]\n",
    "    n_wide_points = datapoints.shape[0] - win_pad * 2\n",
    "    wide_window_len = (2*win_pad + 1) * datapoints.shape[1]\n",
    "    data_wide = np.zeros(shape=(n_wide_points, wide_window_len))\n",
    "    for i in range(win_pad, (len(data_wide) + win_pad)):\n",
    "        if i + 1 % 300 == 0:\n",
    "            print(i + 1)\n",
    "        wide_win = np.concatenate(datapoints[i - win_pad:i + win_pad + 1])\n",
    "        data_wide[i - win_pad] = wide_win\n",
    "    return data_wide, labels"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:30:15.778170032Z",
     "start_time": "2023-08-22T14:30:15.737670311Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [],
   "source": [
    "def get_r_peaks(data):\n",
    "    r_peaks_wide = []\n",
    "    for d in data:\n",
    "        try:\n",
    "            new_peaks = neurokit2.ecg_peaks(d, sampling_rate=500)[1]['ECG_R_Peaks']\n",
    "            r_peaks_wide.append(new_peaks)\n",
    "        except:\n",
    "            r_peaks_wide.append([])\n",
    "    return r_peaks_wide"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:30:15.801934563Z",
     "start_time": "2023-08-22T14:30:15.745355861Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [],
   "source": [
    "#if detected bpm is less than 30 sth is off\n",
    "#most commoom beat is one every seconde if there is less than\n",
    "def where_not_30bpm(peaks_list, len_data):\n",
    "    nr_seconds = len_data / 500\n",
    "    where_less_than_half = np.array([len(p) > (nr_seconds / 2) for p in peaks_list])\n",
    "    prcnt_discarded = sum(where_less_than_half) / len(where_less_than_half)\n",
    "\n",
    "    print(prcnt_discarded * 100)\n",
    "    return where_less_than_half"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:30:15.802368888Z",
     "start_time": "2023-08-22T14:30:15.791356698Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [],
   "source": [
    "def normalize_1(x):\n",
    "    normalized = (2*((x-min(x))/(max(x)- min(x)))-1)\n",
    "    return normalized\n",
    "def normalize_0(x):\n",
    "    normalized = (x-min(x))/(max(x)-min(x))\n",
    "    return normalized"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:30:15.802629651Z",
     "start_time": "2023-08-22T14:30:15.791655351Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [],
   "source": [
    "data_wide, labels_wide= make_wide_windows(data, labels, win_pad=2)\n",
    "r_peaks_wide = get_r_peaks(data_wide)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:19.696728767Z",
     "start_time": "2023-08-22T14:30:15.791886224Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "19244"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data_wide)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:19.741876952Z",
     "start_time": "2023-08-22T14:31:19.739231580Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "99.62585741010184\n"
     ]
    }
   ],
   "source": [
    "where_more_than_30bpm = where_not_30bpm(r_peaks_wide, len_data=data_wide.shape[1])\n",
    "# removing bad data from datapoints, labels and peaks\n",
    "data_filtered = remove_from_data(data_wide, where_more_than_30bpm)\n",
    "labels_filtered = remove_from_data(labels_wide, where_more_than_30bpm)\n",
    "r_peaks_filtered = remove_from_data(r_peaks_wide, where_more_than_30bpm)\n",
    "# calculating differences\n",
    "r_peaks_diffs = [np.diff(d) for d in r_peaks_filtered]\n",
    "assert(len(r_peaks_diffs) == len(labels_filtered))"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:22.593799581Z",
     "start_time": "2023-08-22T14:31:19.739632385Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [],
   "source": [
    "def calculate_cwt(data, scales = np.arange(1,100), wavelet = 'cmor'):\n",
    "    coef_p, freq_p = pywt.cwt(data, scales, wavelet)\n",
    "    abs_coefs = np.abs(coef_p)\n",
    "    return abs_coefs\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:22.639239651Z",
     "start_time": "2023-08-22T14:31:22.595425791Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "CWT from calculations"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "Counter({0: 3519, 1: 1127, 2: 8844, 3: 975, 4: 1310, 5: 3473})"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from collections import Counter\n",
    "Counter(labels)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:23.003871522Z",
     "start_time": "2023-08-22T14:31:22.915548934Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [],
   "source": [
    "# take only stage 2 and 5"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:23.004083985Z",
     "start_time": "2023-08-22T14:31:22.959371614Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "data": {
      "text/plain": "(array([  299,   300,   301, ..., 19166, 19167, 19168]),)"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "where2 = np.where(labels_filtered == 2)\n",
    "where5 = np.where(labels_filtered == 5)\n",
    "where5"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:23.004326748Z",
     "start_time": "2023-08-22T14:31:22.959682188Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19168\n"
     ]
    }
   ],
   "source": [
    "print(max(where5[0]))"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:23.004536510Z",
     "start_time": "2023-08-22T14:31:22.959961171Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "19172"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(r_peaks_diffs)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:23.004755663Z",
     "start_time": "2023-08-22T14:31:22.960258005Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [],
   "source": [
    "r_peaks_diffs_5 = [r_peaks_diffs[i] for i in where5[0]]\n",
    "r_peaks_diffs_2 = [r_peaks_diffs[i] for i in where2[0]]"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:31:23.004888845Z",
     "start_time": "2023-08-22T14:31:22.960601669Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [],
   "source": [
    "wavelet_name = 'cmor'\n",
    "scales = np.linspace(1, 100, 128)\n",
    "images_5 = [calculate_cwt(d, wavelet=wavelet_name, scales=scales) for d in r_peaks_diffs_5]\n",
    "#np.save('images/cwt_5_100s', images_5)\n",
    "images_2 = [calculate_cwt(d) for d in r_peaks_diffs_2]\n",
    "    #np.save('images/cwt_2_100s', images_2)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:33:01.713461450Z",
     "start_time": "2023-08-22T14:31:22.960973084Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "outputs": [],
   "source": [
    "from PIL import Image\n",
    "def save_as_images(im_list, stage):\n",
    "    dir = 'images/' + f'cwt_{wavelet_name}_scales{max(scales)}_{len(scales)}_tiff/'\n",
    "    if not os.path.exists(dir):\n",
    "        os.mkdir(dir)\n",
    "    if not os.path.exists(dir+f'{stage}/'):\n",
    "        os.mkdir(dir+f'{stage}/')\n",
    "    for ind, im in enumerate(im_list):\n",
    "        im = Image.fromarray(im)\n",
    "        im = im.convert('L')\n",
    "        im.save(dir+f'/{stage}/' + str(ind) + '.tiff')\n",
    "\n",
    "def save_as_np(im_list, stage):\n",
    "    dir = 'images/' + f'cwt_{wavelet_name}_scales{max(scales)}_{len(scales)}_np/'\n",
    "    if not os.path.exists(dir):\n",
    "        os.mkdir(dir)\n",
    "    if not os.path.exists(dir+f'{stage}/'):\n",
    "        os.mkdir(dir+f'{stage}/')\n",
    "    # if i want to have them all in a single np array i have to do padding to the biggest here\n",
    "    # with np.pad\n",
    "    # getting biggest shape with max(im_list, key=lambda x: x.shape).shape\n",
    "    max_shape = max(im_list, key=lambda x: x.shape).shape\n",
    "\n",
    "    to_save = np.empty((len(im_list),*max_shape))\n",
    "\n",
    "    for ind, im in enumerate(im_list):\n",
    "        shape_diff = max_shape[1]- im.shape[1]\n",
    "        if shape_diff%2 == 0:\n",
    "            padding = (shape_diff//2, shape_diff//2)\n",
    "        else:\n",
    "            padding = ((shape_diff//2)+1, shape_diff//2)\n",
    "        padded_arr = np.pad(im, ((0,0),padding))\n",
    "        to_save[ind] = padded_arr\n",
    "    np.save(f'{stage}', to_save)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T16:49:01.669784234Z",
     "start_time": "2023-08-22T16:49:01.651309121Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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hx44diwMHDmDSpEn44Ycf8O6772L+/Pl4+umn/WHGjx+PlStXYubMmdi1axdmzpyJVatWYcKECf4wZ86cwZYtW7BlyxYAtW4VtmzZ4ne7cObMGTz99NPIy8vD/v37sWbNGtx1111ISEjAPffcAwCIj4/HqFGj8NRTT+Grr75CYWEhHnroIXTs2BF9+/blWWy2UnDwlNNZEDgASbhRG2ArLlTj612lhk5VunWwdppQFypzdx7DO9/8ZDkeK+1n3/EzOH660m+CIGDD4ZPnsHrXMVvvdK1zWbKp6GcMnr3OtR7jo3hGPnLkSJw4cQLTp09HcXEx0tLSsGLFCrRq1QpArYYn0KdUamoqVqxYgYkTJ+KNN95AcnIyZs+ejXvvvdcfplu3bliyZAmeeeYZTJ06FW3atMHSpUvRtWtXf5jNmzejd+/e/s+TJk0CADzyyCNYsGABIiMjsW3bNixcuBCnTp1C8+bN0bt3byxduhQNGzb0P/fqq68iKioKI0aMwPnz59GnTx//86GKXROgly5YDhfUquTBdzZi25FyjO/TFhP7XcckrUM/n8O/Nh/CI92uQdMrYpnEGe644aj5mIW1V1SlX9MYXVo21gltP24ZdUrKL2Dumr14OLMVrm3WUP8BF3D7zK8BAO/95mb0btfM1rRHvFXrKX74vA0omjHY1rRp4CpIAcC4ceMwbtw44m8LFixQfNezZ08UFGgbog0fPhzDhw9X/b1Xr16aE3W9evXw5ZdfaqYBAHFxcXj99dfx+uuv64Z1G+eqLmJZ/mH07ZCI5vH1nM6OwCJOani2/eLdeHnhEdOClHy76565G1B2phJbD5fj/UdvsZxHVmw7XI6n/rUF2YPao/f19k4WtNi9BjGTXmmFux05+nFIsvr9BwXIP3AS/84/jJ3T73QmEzQQymfT/p9tF6TqcOv6W9y1F6K8sOIHTP1kB4bO+Z/TWTHNsvzDhk4GOoWRzv3F9mKMX1Jo2gfPheoaT17ZIV/YlP3iMXlTUa09SmnFBbz3vyJDHsvNDqpaz/3fgu/w47Ezjt4JGIoYNaI3UrcnzlTi0M/sLtxmzdFT5/HreRuCfKzVXSx9rkq/Lxspi5pLEr7YXoLS06HrYy0QtwhWQpAKUdbsPg6A/pSE2yg7U4mn/rUVj39Q6EqP52a3UcYuKsAnW47inW8u+9+hPV1UdfES2v/5C6T/ZRWTrVE32THd9863eO4/O/HHf39v6Lkfj53Gkx8WMnOuetrE1TNugZs/LIvt5J1vfkLatC+53duW/vwqdH/pa79w7jamfrwd3+0/id8t5n/kf2HefoxdlI/+r35D/YxbhgE3jUdGEYKUwDRG5nKjnSTw9NIlTssOs9Gy6O91g/72I+VoP/ULvPG1vmPCI6fOQ5Jq/cdUuVC4tMJPx2uPnK/eVaoZTi7A3vvmBny69Siy/r5R5Qn78YL9X9mZSvxokzH2X1f8gHNVNZj6yXbFb0aL6kzlRdWrgex6HxJa73HqvH3C+Vc/1PYfLceYhspcZ7C7WHNJuIuAEKTCCkmS8Md/f4831+yjfoZWaFi/pwyPLvgOR09ddrB35NR5vwpbEa+KZOXUFLRiWzGGv7kBRwLyf/x0JXZyvuB26ifbUVVzCX/7UtujuwfmZn5oNMI6gftoOf1WBquVL08HmixX5y9+vgvjFucHCXgZz69C/1e/CfIfV1R2VnWLzA3aggvVNUh79kukPfulJ4TVcOB3iwvQ6+U1WF542OmsOIoQpDyKmYGt4OBJLN18CDO/2MU8Pw/N34jVu0rxx2WXt2Zue3E17pqz3jYv7CRot+DGLS7A5gMngxwl3vzXVRg0ex32iGPUIQ3NltjaH48HaTzOVl5E5oyvNK/nMLP9y2N7bt7afVixrYTo6qTwYO1x8jO/OArt/tLXrnUKevhkrZB3kWX+dKroja/3YjrBezsvOc6IgOgC2Ra5O48BgN9UQW9ecsPJUh4IQSqMYG3YSKKEoBn4oZheENHrZlUXjXssNkI5QQ2/2QW+S1hrBKxGV11zCV/vLlW1KeI20Tigs9xVUoFH3t0UZHfy+fYSlJ6utHxhrJ1o2RoGXgDtTjHKRgIK4G9f7sa7/yvC3lL+F5znrPoRt8/8mtqulbaeTpypxMwvdqneXhH29c0AIUgJPMOF6hp0+Usu+s1ayyQ+N2xXWKHmkoQNe8sMnXRjxeur9+L/3vsOWfM38U9MZaS3q/52l3DWSBLeI9x3rtzWN9XssliSs2oPjpw6T2UvaYSn/7UVb67Zh7teXw+Ab9nK263is4bYRmrzXukHQpASaKLVju0e7HaXnMaZyov4yWHjRgnOaEbkLNiwHw/8fSNGvnX5nsHSigs4G3CZaVHZWbz85W6cPBt8kbDV3C/Lr7WJ2EJxhYMZe5aisrPcTnnJsfOuvfDBuXf3+vYRa/uvOm/gXrjk2KsIQcqjsOpr8iHHbStBL+BUmdUZeP5QXGsQX1pxAbe88BVumr7SH2bw7HWY8/Ve/D+CWwF5G9J7DyOCgdUy6f3yGgx5fb0l9x3fHz6F22euxooA/z2uxGBfVgvudQHCNVAUo5193tEx2aKWyGrevTIfCUFKYAtOqWjt0gq4ob/XrTyray6/c51dXMFB5+28SOjVT52BMfFZnap9bGE+Dp88j3E2+O8JZSSJX/91fKJktSB1+j0EjiIEqTDHC5sPbt8ndyJ/bi8TOWruLnhywYQHeKcnRLdolZwuByt4YkvVw+UrUCIEqRDFywMh4P5xRj7hGR26zQz2rMtE3kb0hDM7Jnm9UmGRB633ZCGgOiE0ssZ6OSjLgLsxsQfkJz8G8mrnVppb0vAaQpAKUezQWFjp4G7oi27Q6rihHOxAzYDWLRoYlrjVWaRpT/4urCKXFjERFxZfEG7PnxcQgpRAE16dTG0cdHp8JE2CXhq0Bd6mTlOpJbyo/WRGy0nbtu0Wpsj5cu+Ur6nltC8bjhEO76iFEKTCCDdszdiNWzUe5rxehz7EUnFnFeri1ranh1s1arrYWNxuKCI3ti4rns3dqPmkRQhSHsVbjc7ESjng3956V3twe5m4YaKhRU+TQ7J5Ylr8LqhLF2TBPTjcdq0kz7zfhZlwahYhSIURdpxmEQOywO24XQgNVYyUO6s68qx2jSHyhQAPTalajF7VyhpFCFICV6HV7cQEaB75hOKVCUYrl6TfKi/W4FyVez0482zCZiatuj7FvjXwaF90cRoqBw+PKaxK2M0jgUeGKSFIhTv2jCPWUrHTGaDdR9dpX400ObBe7bH0bB78nH1kPL8KHf78JS5U1zArHbcJnWZzIxYi4YliEWXI9wIpPosZCkGEICVwJaQx36kO7NYJSD4guimftHlhvd18+kKtNmr/Cfr7GAMFUvp804QhnAClzJOTk1Uo+MFSwwtCQOiWvvH+7pWmKASpEIWZjYENaYQCZovC7HNevildC+IrhMB7uQGz7YNVu2LZPpm1E9IzdoxrnNIQY7IzCEFKYBorA6Nd/d3oCsiubRzD+YLEtMx8Pp+thqA8tBwhM2e4UFC0a0J24aszJ2TaKQXy4ZP3ASe3tB8hSHmUUNA+OA1tGYZqWXviTjIO8L4ixkvtRS2v7nwH6yIJKwHRTs0P77SMRi+0XkqEICWwBdq+58rxmwK355tGI+TEXXteOB7thM2Qk5OVXCtrLi/ur1dH4XTXnlNYOTQTCghBKkQhdT5SI9a/JJYNTo0FodpxvYbZLVMrtcezzdHky0ttzzs51SdcNK2hVGdeRwhSHsWt6lXyEBYeA5vgMkxX0S5t62oY7pseez+WaFwYYmMuZFC0XZ5aIubOyW2cLJSX09On7WUBWAhSAoFH8O4wQ4982DXqkFPgFqzWDpvadcO2mAuyEISXNKV6uOVNhCAlcAQzg4tbtXBmsDqYGS0Lr3o2N4skGbHLs68sQqgJuw9f3f9EKXsRoumJR4YpIUiFEaQJg/WQEw5DGMvObUXtLh94rAqa3Dyba52Sc916PXQJpbIO9YWAmyHb34Y3QpASCDyI2+cRN2sPtfLm5nzzIKTe14xtUyi9v8AxhCAVorh9gFS/Ldx7sHaWSUzDwFaVl3G5fBiyaNqieciw2jMZYNCZw+HSYrfPY3VwF6Tmzp2L1NRUxMXFIT09HevWrdMMv3btWqSnpyMuLg6tW7fGvHnzFGGWLVuGDh06IDY2Fh06dMDy5cuDfv/mm29w1113ITk5GT6fDx9//HHQ79XV1fjjH/+Ijh07okGDBkhOTsbDDz+Mo0ePBoXr1atXrQfogL/77rvPXEEIXIeV++CsdnAW2yxW4whnWxKntob0UuWZLSP17ZUJzAs4XZRiG5Q/XAWppUuXYsKECZgyZQoKCwvRvXt3DBw4EAcPHiSGLyoqwqBBg9C9e3cUFhZi8uTJePLJJ7Fs2TJ/mLy8PIwcORJZWVnYunUrsrKyMGLECGzcuNEf5uzZs+jUqRPmzJlDTOfcuXMoKCjA1KlTUVBQgI8++gg//vgjhg4dqgg7ZswYFBcX+//eeusti6XiLdh0QTZDCevxINTGFze/jx1HsAMnDCPJ8RIorQi6tl2hRLqzUeX7sMFhycdpwcsMTjUXtzTTKJ6Rz5o1C6NGjcLo0aMBADk5Ofjyyy/x5ptvYsaMGYrw8+bNQ8uWLZGTkwMAaN++PTZv3oyXX34Z9957rz+Ofv36ITs7GwCQnZ2NtWvXIicnBx9++CEAYODAgRg4cKBqvuLj45Gbmxv03euvv45bbrkFBw8eRMuWLf3f169fH0lJSeYLQQAg9D2b80ZoCNjhhSti7O4HWs1LtL3QhucVMeHSdrhppKqqqpCfn4/+/fsHfd+/f39s2LCB+ExeXp4i/IABA7B582ZUV1drhlGLk5by8nL4fD5ceeWVQd8vXrwYCQkJuOGGG/D000/j9OnTltJxEjMr7zDpB5qQTsexWrGHqtqd12t56eRZaG2d2v0u7nbIyeAR6rh4tnk3jT9e6ttyuGmkysrKUFNTg8TExKDvExMTUVJSQnympKSEGP7ixYsoKytD8+bNVcOoxUnDhQsX8Kc//QkPPPAAGjVq5P/+wQcfRGpqKpKSkrB9+3ZkZ2dj69atCm1WIJWVlaisrPR/rqioMJ0vLdw6SHu3K5jHB19YvDdtmzMyNuvFaXacd9H8IBBwgXYGcOKuyDrCpR9y3doDlJUoSZJmxZLCy783GqcW1dXVuO+++3Dp0iXMnTs36LcxY8b4/52Wloa2bdsiIyMDBQUF6NKlCzG+GTNm4LnnnjOVl9CFkaWVO2VHzyJfAXI9neXAiOrkBGIWK1n24OtyR+HtgFMZGY6W4WJD4DzctvYSEhIQGRmp0BSVlpYqNEp1JCUlEcNHRUWhadOmmmHU4tSiuroaI0aMQFFREXJzc4O0USS6dOmC6Oho7NmzRzVMdnY2ysvL/X+HDh0ynC8a9NSgXl8JhMuk4MXJXuAsZoVSa1sn7hpQtHIjuhQ7vLzdZifcBKmYmBikp6crtsFyc3PRrVs34jOZmZmK8CtXrkRGRgaio6M1w6jFqUadELVnzx6sWrXKL6hpsWPHDlRXV6N58+aqYWJjY9GoUaOgP4GAB6w9mzuBfKB24hUC88C7DD1YRcywa0p22yLSZdmxjJ3l67a6VIPr1t6kSZOQlZWFjIwMZGZm4u2338bBgwcxduxYALXamyNHjmDhwoUAgLFjx2LOnDmYNGkSxowZg7y8PMyfP99/Gg8Axo8fjx49emDmzJm4++678cknn2DVqlVYv369P8yZM2ewd+9e/+eioiJs2bIFTZo0QcuWLXHx4kUMHz4cBQUF+O9//4uamhq/lqtJkyaIiYnBvn37sHjxYgwaNAgJCQnYuXMnnnrqKXTu3Bm33XYbz2ILSRT9waUzCk2/ZdG5jarr7RhQWF0RI4/HkhsAC+3ETYa0duDF17W7jrxYRgL3w1WQGjlyJE6cOIHp06ejuLgYaWlpWLFiBVq1agUAKC4uDvIplZqaihUrVmDixIl44403kJycjNmzZ/tdHwBAt27dsGTJEjzzzDOYOnUq2rRpg6VLl6Jr167+MJs3b0bv3r39nydNmgQAeOSRR7BgwQIcPnwYn376KQDgpptuCsrz119/jV69eiEmJgZfffUVXnvtNZw5cwYpKSkYPHgwnn32WURGRjIvK9aQJiA71LQulY8sobuNGnJrTuuYFYDcWJI8j4fLceNE70ye2DvBdRUeeRfaBR+L1/GyLRh3Y/Nx48Zh3LhxxN8WLFig+K5nz54oKCjQjHP48OEYPny46u+9evXSXOlcc801uiuhlJQUrF27VjOMwAIunDCsYHQIcIPw5eWBS8AXu4SWcLARDP035Ide83BL2Yq79gSuoq5juHFl7jbcIIx5ERZzdyjbUvHqe26Z9EIFN/V+tbzI+0moys1CkAojvKCBcNPgIGAHD82DFfsavq4eNH7jlyxTxEJG4AXc0kyFICXQhtEEyCIWM4O70ey7X9RUx02THzvP72zi0YozcIGhdvccT+xa4JhNx8wQYL3elIm6qX2HCnaXqfYiw7sVLAQpgTZMepqJq2m8LNEYwLbLaW1Kx0kUAlKINiK192J16lIlVQvPssdtQhXP7KjVm9kasdotQrRbWUIIUh7Frdt0PAcU0YG9AetJLtSrnTRRukxO8Cy83CuES/14WUtkJ0KQEtiAc53RrstzuW//UEgT/A2g2Sfg1gWBm/GCfyyy+xXn0hYIeCIEKYEzuHSwMzPY2yEMSBLhBIxbC5GA2uRPs+INDMFbhqCdhM3mwzs15j70ty49hKcyG4zwbK5ECFLhjhjZBZS4Tc3PygZK771EF+GHF7RrbkMUmfsQgpRAYBErAkaojIlaE6IY+L2NqD99DAvbQjoPKYQg5VHcph0Q8MfKhGb3uB3qdipufD8z7YP0iASJ8H7uH2/MVInZcdTO6me9he+kYOzGfsMCIUiFO2F8worlq3vpvUOFUNaC2S/4hk4L9nrd62FnVTlth+mVZikEKYHrCeWB0SPjhALDjk69MiI6gG2TVQj1Izs08k7ZbzF3H+KRrmeqH7ikTQtBSuBK9DoV7SDnlUHEDE5u72oVv88X2sKvWzHT1tUesVp/Xql/0jgTTmYTEtyzyPFyuQtBSqCNSzoZ4Lya2ct4d4jig1p5sBQAnPSlxJLa97De95zovXaVt5vrVenxX/67m3PvDYQg5VFCXaiwY3Xi5RIMp7GPdz2Fel+iwY7J1CsOOd3WHhzVPBPSdtHa2jWDuBCkBKYhDb40Xd7soO3UgOIGoaVWBe90LuhwQ3mZLSuWZczPq75JXNh+WG4r2dnsXNDEPYkbxgYeCEFKEIRiYAvVlh8CuG3l7DReaKmkGgtcIHjhHVgitpWUeGXBREMIvYomQpAKUcQkay9iOmCEKEgBV7zfwJyWPcUVMUqEIBXuWJC33HLaQwseHVHiFG8oE2qaB95N30kjaXlVmak6DwwNAgEzhCAVonj5KKldOFlCdZMT7YTDY17iOdnZMZFq1Z+Ryd9rfcV00Wq6rPDJPptNxB68JJe7vSxZEO7uaIQgJQjCjZoDpye6UO38VuBWJoSrSczWPs9qY+omISCnPtn/wxW7+pzTY4sdiPGLP0KQCiPs6FCskvCajZe3chsaiDJ3L06sx5wUnLXSNloW9toguUeQJGXFK0KgEKTCCBf1GVVoOzbtu7i1I5rJF+v6Yxmfnl2NF+zpWOGBbhbG6LfDcNBSsUatf3MvSZdUlRCkBNowmgBZTKRe01LxxOnB3gtCuRp2lZ2XZUcu9etAo+GVpJ1VKx/3/O2K0MDMjLNaz4gxlw4hSIU7Dk2Iat3Tac0FaeBVaFc4p0cMB5qJmT5nXhaE7MbOJml3tdC8mi0mARTu6/SywbrsjB1YCE3sXLB5eeEhBCmBacx6NheENqwHXw+PrwpYlEwo9TGn34VW46IQ9DjkRQ3V/uTQasiIwBNKfVcLIUgJuONW7UfodXKXFrQGzhgl+1xlZBs2eETlEGrbWXpNXfQF6whBKkQxOxjw2loL7Kxm+63TdkHhDrWBv5WJSJGGelx62aFtLawnzrrYzGxPcUUj8fCZTL3/nlpVZcvl08KzuQIhSIU7Do3sRvqHnZ3J7tN0Ti3SSek6sRLXf3/nR1IvH8sOgmT/R/OYDVVAk4bzLYEdXmw+AnWEICXQhsEo6tZJx+ybMbFzccGsYLReAsMbedapd3Vps3MlXvNs7iWs9DOvED4aTTJCkAojvNhBvUJ4DyNKlKew7NhyMJeGG7eMw6Wvqp/etSd9p+qe1fVGNIR0W3LJuwlBKkSxY4Bw2lWBgB66rRP3CRThiqmLgtlnQ/ALoapwcdNrebmMuQtSc+fORWpqKuLi4pCeno5169Zphl+7di3S09MRFxeH1q1bY968eYowy5YtQ4cOHRAbG4sOHTpg+fLlQb9/8803uOuuu5CcnAyfz4ePP/5YEYckSZg2bRqSk5NRr1499OrVCzt27AgKU1lZiSeeeAIJCQlo0KABhg4disOHDxsvBAE11J7NOefDaPp2T2JeHnQEYYpHGq2XFxRht7h1SVVxFaSWLl2KCRMmYMqUKSgsLET37t0xcOBAHDx4kBi+qKgIgwYNQvfu3VFYWIjJkyfjySefxLJly/xh8vLyMHLkSGRlZWHr1q3IysrCiBEjsHHjRn+Ys2fPolOnTpgzZ45q3l566SXMmjULc+bMwXfffYekpCT069cPp0+f9oeZMGECli9fjiVLlmD9+vU4c+YMhgwZgpqaGgalE5rwdLRphzG0KU2ATWOXl49lU9e/C1/RaP26ZGwPOcw0DTcIRW6XH7X6ptW8Wx0bvSIXchWkZs2ahVGjRmH06NFo3749cnJykJKSgjfffJMYft68eWjZsiVycnLQvn17jB49Go8++ihefvllf5icnBz069cP2dnZaNeuHbKzs9GnTx/k5OT4wwwcOBDPP/88hg0bRkxHkiTk5ORgypQpGDZsGNLS0vD+++/j3Llz+OCDDwAA5eXlmD9/Pl555RX07dsXnTt3xqJFi7Bt2zasWrWKXSHZCNX2jvKSNPqwBvBI/3AV+pNCaHo2D8wqi3xrlSNLYdUrkwAJA8MAE1jG7+FiN4aLGljYacJkcBOkqqqqkJ+fj/79+wd9379/f2zYsIH4TF5eniL8gAEDsHnzZlRXV2uGUYuTRFFREUpKSoLiiY2NRc+ePf3x5Ofno7q6OihMcnIy0tLSNNOqrKxERUVF0B8Pwrzdeh4W9edkG2AliFlyHaEVr0lNBO1zbhREXZglXbyYZ6exs9+LeYYOboJUWVkZampqkJiYGPR9YmIiSkpKiM+UlJQQw1+8eBFlZWWaYdTiVEun7jm1eEpKShATE4PGjRsbSmvGjBmIj4/3/6WkpFDnKxSwOjCG28rGigbEyGROKlZewoBdV8SISdgYpPLyam8zdA+e6dOc7sCNQjstXs67Ebgbm8snRkmStG+bJoSXf280TlZ5owmTnZ2N8vJy/9+hQ4cM54sFbvJsbrUzhUlfdD2aHpUNhNVOhFE8nAkVeZ9UvDQXd7sZHll1ZX17qVJ+wY3FyAJuglRCQgIiIyMV2pvS0lKFJqiOpKQkYvioqCg0bdpUM4xanGrpANCMJykpCVVVVTh58qShtGJjY9GoUaOgPx54sA/5ocm6LTfOM4rHPXVhLSNGhG9XTiwytPLomipzCZrVGcKFRWrzdhzqMJKC0icb06wwgYWfODu15qzhJkjFxMQgPT0dubm5Qd/n5uaiW7duxGcyMzMV4VeuXImMjAxER0drhlGLk0RqaiqSkpKC4qmqqsLatWv98aSnpyM6OjooTHFxMbZv324oLYF7cbKPumGACHWnh2rIJ0qnT0MSr+txWFDlkr7TL+UQbn/tcPdKzoIonpFPmjQJWVlZyMjIQGZmJt5++20cPHgQY8eOBVC7DXbkyBEsXLgQADB27FjMmTMHkyZNwpgxY5CXl4f58+fjww8/9Mc5fvx49OjRAzNnzsTdd9+NTz75BKtWrcL69ev9Yc6cOYO9e/f6PxcVFWHLli1o0qQJWrZsCZ/PhwkTJuCFF15A27Zt0bZtW7zwwguoX78+HnjgAQBAfHw8Ro0ahaeeegpNmzZFkyZN8PTTT6Njx47o27cvz2Ljhts7tB5um5BZEIrvBNC3Na+3SS3snp/0ilLbOJ8todmq7SFUxwTAXo/udsJVkBo5ciROnDiB6dOno7i4GGlpaVixYgVatWoFoFbDE+hTKjU1FStWrMDEiRPxxhtvIDk5GbNnz8a9997rD9OtWzcsWbIEzzzzDKZOnYo2bdpg6dKl6Nq1qz/M5s2b0bt3b//nSZMmAQAeeeQRLFiwAADwhz/8AefPn8e4ceNw8uRJdO3aFStXrkTDhg39z7366quIiorCiBEjcP78efTp0wcLFixAZGQkl/JyJYxaN+tVT218ITwL62C0NFkUv5eEHiNaJqcnLi9PIIZw4YuS6p74nfuyzoRQfS+74SpIAcC4ceMwbtw44m91Qk0gPXv2REFBgWacw4cPx/Dhw1V/79Wrl+7E7fP5MG3aNEybNk01TFxcHF5//XW8/vrrmnEJ2FFXb6TqM7MFw2Lud8NYI0nOb0HR4hZfTF68LDlUtlmMlkGIvDYTvNLPafDS4ssK4q69EMXpVXYg4dKZnMdaQbupzZiBRe5ZTGLeLkXv4qXThi7NlgK3ll8dbhmzhCAl0IaRFOSUfyh3dDN1Qmn16SbcMMBya/ImX81KibjvXbS804cJHh+baXBx1oIQgpRHcWsDc2m2mOOGLRi3tgEjKIrRwDuZrQI3CFl6ON28bDeU93pbdrrCwhS3LESFIBVG2NHXeSThBqFFC89PAoxhKahIkr3lS5t3twzgPLBV0GR5x55Lq8Tlw5eAAUKQClFMezZnnA/A3EDi1kGRFUbfz+dTTnB2D9C2pMcwDTe2Ib08WdlmMVN0/psjTKfqLZi1YQelI3e2a7pMuTDrTBCClMBVuHm/Xg2x4uRLYPl6YVsu1AjXMjekCde89ozwnaF8aH/Ww8qISjsck65yY4FXxlYhSIU5cs2VLUoHt/QOyny4RUvHGvl7eW27ykmZ26xwQXTr4aBnc7WJz2r6li8vt/g8a9y4vewN3FaTfBCCVBjhQWWP7dAMYU4IgspVqfU82PUWbhAa5RhSNnhkMnB7Li0LVyYHMK26pr1rz41tmJQp97UBNxYce4QgJfAkTLon5cDslqHAzRO6UrBzb17luKlcXaOtlWG7PR6nZxUXAFN6NteNyMVoXssCiWmbc2v75Y0QpASmseaXhjwQse6I3hnuwhMn5iO7BCduc4po1ERCdQ5n3UeMxMe6TEO0ioQg5VVYNfDQ2o93DtNGlh6aFI29onfaVWAfcJN2yk7sqC2WJRuqQpPAmwhBSuB6vDBmek2lbbcA7WWDfaNlVZcv+hNPhjPkeqjrm8O7hI0oTGhgZorTiyel63CLIkAIUh7Fa23fK9llcsmxTTM86zbAc1BSi1mvqKzliF+rCzfNFe/xhiZ6Vy9WDOZN044rzNqWFl6Z54QgJeBOrTPJYFw9KOrAdAXn0WLwxgBHLlzeq1hvlI06TnRNj3YDgS4+jU+hgxCkBEEYaehe6BRigGaHExOsDxy3yEhxhFmLCTfP5szw8ELQatbDrY/QIAQpAXc8POZQEeKvJ2CIk8437cQJh5w05eiWschKlWsJMqR4Q7B5uQ4hSIU5Yb0fTxhViUMUbTiuSIpPRiYF0laqFc/mbpmQ7MArfYSXQMbuhLA1vGwUbQSn79S0Auu7Ir3y7kKQEtiOtsM8SieZLupgXhzevSIcCOhxU58IBdxanCz7rl6bId8T6J6xwy15EYKUwDQ8HHJqP2MhQYYwNZSnfieXvLwJnJiQ3CpUOJkv8j1/3mxXXtZeOI1Hq9zVCEFK4CqEZ3PzuGuA5LNq5j1ZumWFGzZwLm7bhCsnOp8NLyeEUzqEICUIwo39ht9VG5SDn7skFFUM2Uy5pKadKlq3vL8ZvJx3BTwccnqju9pGCLUW1yIEKYGAAW7fIiHlzwsDrFsdcmrh92zuSOqhAcu26YV2bgqXjzmAsSyaeRu3LCqEICXQhFVXZeMxnEEkNmBXPu0eRwPTk6et98pqWSWVFW9nrbZdWmxLKuxxIt923cPHrM94QIhxA14Zs60iBKkQRfRze/Gyp3Y3wWqFKdq/ElKZ8Gq3YefPiGP/91JbZm7j6pF3F4JUmCOfuOTtVogHgjqsjJHWTnhaeJiAW7YDBOp4ZP50HWR3BWwR/UeJEKRCFKEgYYhOYdpT1Pyd9LEaIGvz5s0G6IV7+LxwspDonsBinK4yDzAQEev60mqjYtx3BiFIhRHuH35txsFRpy5lQ3cbWqhAGs/mboDVpOPVCeVyu2DvZ81smbilKAPzIbbS3YnwbC4IeUht0srEZWXKs7oyp9UceKQfugIvaDq0EFsO7LC7LbCoOZ72NE62La8IE6zwopAsBCmBaYw09+DVpLnBwS2Gh25xdSAvQzuzZfWeP0a5sPg7H1zSPMIOZncCMm42bhPwrQrJRp4Pl74gBCmBqyAKKRbGIR79WJIky4NtXb4MCaPuGo9Vqa1CNiVv9zjsFq2c2yZfXvB+T734tfqUW/ubW9qo4DJCkBK4Ci+qdb04rHmlmN3qkNPsSptFuasJB+a0vF5svdrweKVQEl7CRUi3E+6C1Ny5c5Gamoq4uDikp6dj3bp1muHXrl2L9PR0xMXFoXXr1pg3b54izLJly9ChQwfExsaiQ4cOWL58ueF0fT4f8e9vf/ubP0yvXr0Uv993330mS0IgCB1CcP5lhleEVDW8uJhhiWjbAqNwFaSWLl2KCRMmYMqUKSgsLET37t0xcOBAHDx4kBi+qKgIgwYNQvfu3VFYWIjJkyfjySefxLJly/xh8vLyMHLkSGRlZWHr1q3IysrCiBEjsHHjRkPpFhcXB/29++678Pl8uPfee4PyNGbMmKBwb731FuNScjchPaYwHDEDV/Z2uThUeBcP7/nPEHaUlZf6jtJTvb2NyamyEp7O7S17DxeTJlwFqVmzZmHUqFEYPXo02rdvj5ycHKSkpODNN98khp83bx5atmyJnJwctG/fHqNHj8ajjz6Kl19+2R8mJycH/fr1Q3Z2Ntq1a4fs7Gz06dMHOTk5htJNSkoK+vvkk0/Qu3dvtG7dOihP9evXDwoXHx/PtpA44bYG67LshD22Xy9DGY40gQcKPY5cXxLCjZdW+xTCRRBShHJbdTPcBKmqqirk5+ejf//+Qd/3798fGzZsID6Tl5enCD9gwABs3rwZ1dXVmmHq4jST7rFjx/DZZ59h1KhRit8WL16MhIQE3HDDDXj66adx+vRpjbcGKisrUVFREfQnYIMtGheb1Tr0456k+TE8cfes4bYqcto2htS11GyP9Dx0u61svawONppzK+1I8x5E0nfu7uJ+onhFXFZWhpqaGiQmJgZ9n5iYiJKSEuIzJSUlxPAXL15EWVkZmjdvrhqmLk4z6b7//vto2LAhhg0bFvT9gw8+iNTUVCQlJWH79u3Izs7G1q1bkZubq/reM2bMwHPPPaf6e6jjKfsKRnmVYM97e2VQYV0Ubnxvs+/Iy2kmTdxegmUbcnpMIgmLWnWll12nBWIjhFCT1ISbIFWH/FSIJEmaJ0VI4eXf08RpJN13330XDz74IOLi4oK+HzNmjP/faWlpaNu2LTIyMlBQUIAuXboQ48rOzsakSZP8nysqKpCSkkIMazdONWqiI9Bw6WEqeGcoZINX3teJScqIpsYKZuOUJDalYlefd/P1Sf74vNIhLGLW16DX4CZIJSQkIDIyUqEFKi0tVWiL6khKSiKGj4qKQtOmTTXD1MVpNN1169Zh9+7dWLp0qe47denSBdHR0dizZ4+qIBUbG4vY2FjduHhD21F1V8gG0+BxnFrPbkbgPGw1CNQh2SWqlUoYtDWFc1cP6hK8pKlxC25v227PXx3cbKRiYmKQnp6u2AbLzc1Ft27diM9kZmYqwq9cuRIZGRmIjo7WDFMXp9F058+fj/T0dHTq1En3nXbs2IHq6mo0b95cN6xXcGtDJdpI2DG2e1hV5uGs+3F6Anc6fYHzOD0m8u7HRtq4E2XhdPmbgevW3qRJk5CVlYWMjAxkZmbi7bffxsGDBzF27FgAtdtgR44cwcKFCwEAY8eOxZw5czBp0iSMGTMGeXl5mD9/Pj788EN/nOPHj0ePHj0wc+ZM3H333fjkk0+watUqrF+/njrdOioqKvCvf/0Lr7zyiiLv+/btw+LFizFo0CAkJCRg586deOqpp9C5c2fcdtttPIqLO061T3m3FSvH8MJKbbvVZigUhFY3YGQsMNMUvDgpW8Eetx6i8cvhKkiNHDkSJ06cwPTp01FcXIy0tDSsWLECrVq1AlDryynQt1NqaipWrFiBiRMn4o033kBycjJmz54d5NupW7duWLJkCZ555hlMnToVbdq0wdKlS9G1a1fqdOtYsmQJJEnC/fffr8h7TEwMvvrqK7z22ms4c+YMUlJSMHjwYDz77LOIjIxkXVSehOsloWE2AJrBShmFYvmG4jsJ6Kmb4I2MS3a0GbFwDH24G5uPGzcO48aNI/62YMECxXc9e/ZEQUGBZpzDhw/H8OHDTadbx2OPPYbHHnuM+FtKSgrWrl2r+bxAYCdCUHCGcNM+iWZWi1sFIC9rhEK1L4m79gSa8Gr3oSwU0By3NlquZMN+g5G4kBBuBsQ6pm33ZiZxK8fmQ6Et8cSNwgut3yUrB4BsbRcmJgW3zCNCkApRxMBoEkLPJPZV+SknkwVu+vLbEBVBWL6XWwZZI7i1XlkI/kbqQ9chJ8diCrexk+frhktRCkFKEITb7Au8gJXBwurkQhuXnVWlNwnSfK8VF2tCpR2HmwDgJlg2IXqtpTO4Vdh3EiFIhRFuGmdDadCXDyuhOsy4TeBglR872yJtWm7cSgoF5E3Gjrp3ui6teHZ3us97ZZ4QgpSAKTyuY3C6M9NgtMMbfSUeA4rROGnDy+vLav2xnoi80J7chFeKi6emRB63QiAzGJ+V/sx0+9sztetuhCAl4I6ZruqVlUgdbpicrZYZyzL3Wv3xwAVNwjG8XP9u6Mt2YufrapathxuNEKTCHHnbVVwV4d22zQxRBLVY8ltlIc3AVbMRjada23Vbmw5nrYBadYabMBMqWOpapIM+Ou3ALX1ZCFIhCquByGg8PO7as4IT+XHjJGDlKL5bcVlTcz1O2+o4UV9ubeJG+p5b30FwGSFICWzHLafLWMJ7krDFA7ORE4ScJmWnJ3uWuM0HG63mi+i6wFySurDsN6raLRPPCJzDi1UiBKkwgnUDDcktCZuXzaGiVTHbFkhP2d2q3DiZhkq7YElQmZisM5pipYmaq+8lC5Hbcq+7hVRCtV0LQSpEMXvCyi7s6k+GTxHSOuTUisIGUcDpyZ/XO4aCcK7pQVyv5dv8+rySs+qQkzbOQEJ1kjbig41URHaaN3i/95pDCFIC09CuTIx0Y6+OhV7Nty2E6+gaIkgS//Ytn+zNzP1OLy7UYL04YL39rRWbS4vUj1vqXAhSYQoPf09aGPaz5JIOwgu7BS+ni5PH+3qxjfDUuOlNsF4sLydxqrzcXk/8tNHeRQhSYQTNZCYXeNygLue2/cAqHtnI5/aB0CyGXA8wDifQhzTB6dWZW8rfroWd2VR0hVQLz/LGSupuaR9uRwhSAqbQDoh6oazcK2cH8kmLt2dzHvASkiWwfT+zE5GYBMIL4sEFRgMF8+05Bp7NWeTI6XFUDzcs5GkQgpSAO0b6qq2X67KKx0Jvd3q16nZ4XTmkFi2LgZt3nZrNoxvnTD4TOX0BhVJZquHE/YLhhhCkwhy77nxy+8rH7dhRfKE2wNKWWeB7M22nhAIVgjNbwvVuT69g9cSgV+pCCFICpnik3TuOVwYINbQEAiNDp/4WL3/BQ/dYPa+I3RVtQALyj/wbq9F6dpubDJatlPWb6eWN5RZhuC4ThCDlUXhNMHZ1BNvSsWUiNj8U0U4IVAcFDKVrH5ILpj27T6l6DeZH6jl0O327ydCsYyNvxbrYQ7NE2SMEqTCFdswxOsDyOeZuX3cmG6zalrwhwnX1V4fpE1huKziJ+E+7k7YhLfd1JPJ1OKHvUFfAFiFIhRNmnNw5NPjpaZLcOCjXQTdIWss/j7fXy7dTK+PAunZvrYcWVvsXqS2x1HrRCiLsXJwwiogh1C5GNAKaeS3edn5e1CwKQSqcoGifVpuw97qAPnQaDLNH9M0PSsrTOAbtTCxUlhsEWduuGTIc3qHFh6W25EyeeVyU7TqNo41YN+52vl97ESFICWwhnAc3gYAWnvNYuEyS8tdkcN2mrdg9VBpNjyR0h/v4LgQpQRCh1h+0Jg9man/F59CcsLQmGJYn3wLrzMrk78a2zGLCcXqiN4v2Zc7eQp5fllXixer1aptkhRCkPAqrgYd5ByDaRoQ+XlyReTHPPAhsskzLhBCZJyccjnkOB4eYJOzte/YlZqVePNk3fkEIUgJNeBkW2uGWwEw6bu3MNNlyi1yk0NBZLFO1Nsg6HfX07cNubaZb2gwLzJQc0SieUCjy77x4A4MX8cpiTwhSHsVLRuFeyqtXkCSJ+faCrp+egBTc7qHbyjYkz7RpMbPQ0BPCnHZ1oFknHPNiFKJLBDdlkCF2XrgeyjZ6QpAKJyhWWlbh2VW4XeWhAw9jVb8nYHfLI6axS+NoFjWhwy1jPbPLdk1EY6dWTPXOQx1BnfpydJfUJw9oX03eFfU+uwmWLll4IgQpQdhCGj9oJxF5B3fDWMQ7D27XQplF763cPNGwQq9u3VAGunkwsThxw3uxhDim2Sht6PalEB1DhCAlCMIuTUIoq3kFDDUqTGKxF0sXgVP5emNXKrZu92kkZrbIeAwjrGytTKfvwUYfqieVaRGCVIgSinI/6wHGbHQs1M22D5ZE3zr2XRRL+6RXJhGqBQfhZXiuU3RX+ybL1pXer7nG7i54H6rg2eeUdpyhWXPcBam5c+ciNTUVcXFxSE9Px7p16zTDr127Funp6YiLi0Pr1q0xb948RZhly5ahQ4cOiI2NRYcOHbB8+XLD6f7mN7+Bz+cL+rv11luDwlRWVuKJJ55AQkICGjRogKFDh+Lw4cMmSoE9dtzoDehcL2AgkcCwThoC6+F0+lYItW0KllDfLUksQ/uFArfbmIUbes3HaHUxOZBAmQ+vNSUvDsFcBamlS5diwoQJmDJlCgoLC9G9e3cMHDgQBw8eJIYvKirCoEGD0L17dxQWFmLy5Ml48sknsWzZMn+YvLw8jBw5EllZWdi6dSuysrIwYsQIbNy40XC6d955J4qLi/1/K1asCPp9woQJWL58OZYsWYL169fjzJkzGDJkCGpqahiWkjOIrTVv4YPM2B5w7Qhp6DSh3NZMbgir9ajWVpHGg7yPsvvzZerknT787zrjGj03zGg7iO/KugDc2U0BkJwJewu3zGNcBalZs2Zh1KhRGD16NNq3b4+cnBykpKTgzTffJIafN28eWrZsiZycHLRv3x6jR4/Go48+ipdfftkfJicnB/369UN2djbatWuH7Oxs9OnTBzk5OYbTjY2NRVJSkv+vSZMm/t/Ky8sxf/58vPLKK+jbty86d+6MRYsWYdu2bVi1ahXbgrILMyd4DJ9YIz+gPClCP7o43Vf0OquVk1G0xUBMwuaCcboejOClvLoB9qd3KQ9tmJy6zdavaBdKQVx710EUGA3cBKmqqirk5+ejf//+Qd/3798fGzZsID6Tl5enCD9gwABs3rwZ1dXVmmHq4jSS7po1a9CsWTNcd911GDNmDEpLS/2/5efno7q6Oiie5ORkpKWlqeYfqN0OrKioCPrzEi5VcgAgaGQcQtffkoHBh+U4pZkvm+tVLii71hO/AIB+uXrhtBUxjy5tL3aOs26puVDuu9wEqbKyMtTU1CAxMTHo+8TERJSUlBCfKSkpIYa/ePEiysrKNMPUxUmb7sCBA7F48WKsXr0ar7zyCr777jvccccdqKys9KcTExODxo0bU+cfAGbMmIH4+Hj/X0pKimpY2zFnH2srbhTkaLRnXrNpqdUE8KlslrFqxeWxIqeCRghnarCrEpVbTsMZi9+5wYvHiUSauNmnJjBDFO8E5BOMJEmakw4pvPx7mjj1wowcOdL/77S0NGRkZKBVq1b47LPPMGzYMNX86eU/OzsbkyZN8n+uqKhwRJhyqjt5adHhtNBoKx55VzvqhJehbyjDW0gxbKxtID92bx8q0xfQQFpE6LULtyxguWmkEhISEBkZqdDelJaWKrRFdSQlJRHDR0VFoWnTppph6uI0ky4ANG/eHK1atcKePXv86VRVVeHkyZOG4omNjUWjRo2C/njAqv1YicYlbdh18Bo4jZ2SpDNbNpS+odCUuGw3hvYkFO888uha9HZLss8hJAmIMUu7HfC2iTK6ReyVtsdNkIqJiUF6ejpyc3ODvs/NzUW3bt2Iz2RmZirCr1y5EhkZGYiOjtYMUxenmXQB4MSJEzh06BCaN28OAEhPT0d0dHRQPMXFxdi+fbtmPF7DyrFeLup/xw3LzT1n9/gsSfDMrGCXwap8gjBTPE6P21aKypTm5Zcy8khT8iS8ipa2zvTGcC3hxqjGx+525BZjeK5be5MmTUJWVhYyMjKQmZmJt99+GwcPHsTYsWMB1G6DHTlyBAsXLgQAjB07FnPmzMGkSZMwZswY5OXlYf78+fjwww/9cY4fPx49evTAzJkzcffdd+OTTz7BqlWrsH79eup0z5w5g2nTpuHee+9F8+bNsX//fkyePBkJCQm45557AADx8fEYNWoUnnrqKTRt2hRNmjTB008/jY4dO6Jv3748i80W3NH81AnsIE47cdPvrIyOXQsMoX0JLvuTlgJ6yBf/8rXtYnWvoB1Nw4hmRk04Mb/o4yfthGu/4ipIjRw5EidOnMD06dNRXFyMtLQ0rFixAq1atQJQq+EJ9O2UmpqKFStWYOLEiXjjjTeQnJyM2bNn49577/WH6datG5YsWYJnnnkGU6dORZs2bbB06VJ07dqVOt3IyEhs27YNCxcuxKlTp9C8eXP07t0bS5cuRcOGDf3xvPrqq4iKisKIESNw/vx59OnTBwsWLEBkZCTPYnMUqysKaseHJuIOHABYDMpm31XXs7mBrPFawUmSji8li4Op0Xyrhg/hgdduJY/+Rb/84rYKrwnYrkWY04s9XojLoengbmw+btw4jBs3jvjbggULFN/17NkTBQUFmnEOHz4cw4cPN51uvXr18OWXX2o+DwBxcXF4/fXX8frrr+uGtZtwb7i8oC1WeTjeKm2aAU1rslM63vNGA9ITCO2AaDdley4uY8hWjl82uGKlzo08aodbB+PvElxrbliYscCrbZEGcddeGOGWQcP0KRrXdkWfccelfDLiGhTezSlfOJTKxfZ3MdO9OWWSmcZSBUn2f4DhKTuXN0Ke2XPy1V1e7JoIQcqjuPVYqNogJBfi3NBp3D5gWoHqzJ4D94OFOy5WGPiRaz/du4AxjnmP6KFTBk5C05a8qHEVglSIwqrje2HgZ4m5cpM0P9qGjZWlaydmMl5Wr2BWcCe7P7DPPojnfC1kAX64xfO707lw89YiT4QgFUbQrAaM9AMj47KXV7Vu1O54qTydkyvZj+pu1ky4aQ4jn9qj+85s/G6Fl5BF7f5AK33O5WhkXHRT+zWKEKTCFF42K1wm+F+iNDMguX2FRPtORrUi3B3ruaBcNR0L/vIfCTfk3QksGXDb7h/IpnRI7g9MJO6lhY2T7d8tmjvWCEEqzLGjWXvx3i4rODWoGtImmsqi+fey6xQWDfJ3NzNxcnNbYamM+bk/YIETEzg3two2lqWjdwg6lrK3EIKUwBFCbV0SqistuyEN3JJeABsxdBTdQjp2CR12OqTUvthXfleqTlwauWRl0+YlLVMdpFc3Uhx8bfS8V560CEHKo+j1DdJgYsdk77a+YscFtfZctOuygnUBbhVeRV05g98lgkb5u6Vu3LS97Ja8mDrm447qFIKUQBsWfcwtHVWO2RUny/fhterlEatbBi27cWnzVWD1toBA5P6ZvFz3Xs670xhtU25d3PBGCFIC04RLl1F4BWd4RYxppNAtf1blx+XUHvMYZfHz3FrhFzVl+ta2EZlolxmtggydRnNxR/Xi9mUgbilbIUiFOVa6EdGeheERZ3k6rDsNy4nWuGdmiXkeNNPjfDeh5gXCvAx+Na7S4OXnyg04kXeznsd54TaB00taL8sjDmmMtxqnxxGCVJji6EkQrUmXIowRwtV7N+/3sEvlL0HiLmrqaSmcWPV65S4/N+EW+yer8NZ4az1udV7Qe94tGiTWCEFKwBS1jsJa8+KmMVOx9edILuz1wG34WcpScftkaCR/DHzkM4Vl2epeUUVMn1ny1LihNRFP0vFKy4yvPe4PGMOIMOeW4UIIUgKm0DZsM3O+WzoNwGBScsG7yKvAiCDGKvtusNFgLbyxiM1MHKTq03s3p8tfrcXpnpSt+z/h/bTasdm6dr6Vmoe2LI3+ZhQJzpgA2IEQpATByAahUFXFAmrGr/q9WR7GjUXk9ARpFqcu29bCbJbI9/Ypv/NiXblx0mMm3NvhzoR/Eo4gTu0JQh6n5ijyNQwOZMQkRvPKY3uKZvvQavXqay/YxGMHpoUfPe/g5qKlxkrZ8fO2zg+nW8rWQ+UoP1dt+DljjlntG3jD1SbUaYQgFUaQOo0TziZF3+V3ElEvvXAisGwDBRQWZeHkytuJyY/FqT2m20SMCqGk4gJ6v7KGSVzcYFzfWlVpZ9vq/fIalJ+/LMR6WVsrBCmBaQytyqhvKldPxw6hQ6zQ2FN78s5k5UnqWiKz9ha8TxwycWLLIA6zeGXykmO2zH4+WxX02Y63t1K/RutH91SqhbxYoajsLBZvPKAZRq/vuaWlCkEqTLFbYGCeHkejdqO4ceB12v0BrcbAbTYVpHwHTlw0r6VpvMvRv5WVsrRjPNDMnexHVice5fVpJF63L6rc1XPIyMdf+efAMn7vf/uxv+xs8O+uEZW0EYKUIAinO6cXuo1bnT1aERppBB87bJ9YpuH2iZAn3/x4HJcumRcieMB2a0/9N6tjmNNjoB5aArPTZzWspH/w53PoM2stu8zYiBCkPAorda2uPxjDxovumJAvp3X53zM+/0E3vHkjZXPPGcGKoz7yCTL5CU1W12cYcaOg81I+uX0Tf0N+ZRac84BvNu6H392EfxcctiUt1vz5k+1BJb561zF+iZnESU1Jdc0lrvEH9rff/iMfX/0gK3+Tr04z7NdcclrcN4cQpASO4MTK6a21P+HwyXP+zzyuswFqV1a8kSRjZUiz7eE1zLYhK2/tv9qH1wk5hlXyxfYSJvGYaSc1l+gme1LUC/MO4ESA3dKjCzbjmx+PU8dltQhZbSvWwbqtzMr9EbO/2sMkLpp3HfX+5qDPq3eV4vjpSibp65aNR4YoIUiFETQdWqvd7i09Yzg+M2F5cqGa/WpOPhkMm7sBHxceCfqu8mKN7Bn2I4RbytgtaN8NSC5/ln6srERlNB9Z8zcq2qHp5Bk0zYlLt+If3wYbEhtp85dkYTcfOGmbFugv/92Jf24+ZDmegyfUF1RWnd/Oyv1RxQWKfrxWm/ie0jPoIzvp6PVFmVWEICWgpu+stdhy6JT/8/HTlThfVaP+AGPYzHGXO/yOoxVYt0d/pavHgJxvsFa2Yn5zzb6gzxl/WaWwWXESvYGv36y1OHrqPLP01OquukbC+CWFQd8FTZgap/bkSCr/1s2biQAs5o19x8/oB6Jk3Z6yoKPkgLZhrxX++tlOqrimfrzddBoKgUCWYBXn7a0//Pt7zd9pBJYef/vaVNpm6mnG5z9AkiRzwmbAq9z75gYc+lm/31dcuGg8HWLSFk/luUSAE4KUIAi94eHLHcHbBZkvfsUvM7/AciUq73dZ8zfJ0jLHS1/sDvosn8ROV17EmSrzg8/Xu49jZ3EFdXir48ue0jN4YUWwTdnJc9VYsukgOT2tkpOC8yO38fhky1FTeXTk7jaaU3uEMGP/ka+w/+jzylqF/cmXO0pwoZrV4iS4Ecq1olpoCdrvrCsynSNqlPcXBX3s88parNzBZuvSTvIP/Mwl3rfW/oT1e8ssx7PjaAWyl2sLkVag2hVxh2xkCCFICQwhV7mfMuMVWOO3wz+fU51IpCBFBeXxehdtdwVmxcxYMXZRvk78bI+/V15Urvr/9NE2iri0367rC+rCtx1jqDx/Px0/S8xz3r4TFtO5/O8vdpQQ7Xw+lAmmf/tyN56xoMkJRN72xy/Zgre/2UcObIE/f0KXX007Ip1nSb//bnFB0Oexi/IVwhWr9iRvHrTjj1wLfe+bedh+pDzoO7OaX3mZ/Hy2KmgMuPuN/5naMTAzpqvlSY8InQd0hSqXDPBCkPIoVtvPzc+vwq4Seg0HLWSjZp1nAgL8VHYWg2evY5upwLQYPWN1gP5ky1F89n2xpTiMrNyIXu0dctQnd4DoNE/9ayte+nK34vv73/n2l8mJDSSNEKle/p1/mMrmRLl1R/KBFcwLK3YFfWaxQ7Yw7wDVhP3T8bP48dhp4m+KnMvtvVQqQf7cY//QXmyMXZSPHwxodq1SQ6iTwkOnguqq24urcbZSXVtNfwI7OOTWQ6foTm4yXL1oRXX7zNXYc8yYne1D8zcqdkHciBCkQhD5qmzEvDzFyuh05UX8cZm+dkEx2XJQGYx4Ky/o877jwU7Z/t+/vschRifhjAh1VoigkHR//0GBbhizGN0OHTR7nWJl7MRiz0iScrs0K8ht2uo4cYZ8Oslc2fgUWkMJ/LYyaLI4efk2zF9vfauOtr31f/UbxZM08ZH6k5m+eupcNX71xv8MP6eHWlZqLklKNyOEcCUVF9TjtpCvizWXTB264EHp6UpsPnAy6DsaLfpvdYRjNyAEKY+i1f7lq7JN+3/GT2VKw9YqwtaNbro6vxeXX8DpCzSq4csd6Lv9JzXCAev3ltnWmfYdP6s6qRqBfG8UOyRIul6DNZ+XZWZXyWm8+PkucmCXopVfszKg/Dm5RuH9DftN2zDpbWME5UOzMtWED3kcdGn95b87NeORJAqjYMbzMc0JRLNJkrasrTJv7T4qFw11sDwdahlOhxKokrZaDC4xqBKCVIgib16kA2MXKfT68hULTbvv8pdcilDG+KGkwnCnezX3R8V3NHHM/EJboKDpukRBiuH4bcWOgRazNldsBUY2QhFtnohHygMqc8bnuzBn9V6dOOhdK1jRCCjsdhycU0hbWHSQa1chSBGCOSmKkF734Xc3UYXTG4MsHa6RL67MROEiGc8rCEEqRJEP0HIj8TrkkyWLTlRdoz0Q1GbF2GBhJluvMXJaZwbiVgRDEWPga+tQePAUs/hIRDAcHWjb1SUJ2PiT9ZNNPGWKb3+iM0JXaAxBt2VlFoVGykZRg7UQJx+vSEIob61OYA7ufXMDPt1q/HRp7YXd9kBzewENLNukHq7SzFlACFIhinyFaGage/jdTQrfNGaQwH6V4xKNriHsdCOlVz409cFqIj500tipJNLK3kmMao3Uyo2oVWHYLyxpt6yKnhYflxeDvK+4QSP15IeFhp+RJONFw/pKIqNtzMgWtCI9zuHdCndBau7cuUhNTUVcXBzS09Oxbp32iay1a9ciPT0dcXFxaN26NebNm6cIs2zZMnTo0AGxsbHo0KEDli9fbijd6upq/PGPf0THjh3RoEEDJCcn4+GHH8bRo8Erjl69esHn8wX93XfffSZLgi266mFZ7zWzyvjmx+NKnzEOtXyzqySFca+JAd/MBEW06eAo/endv0WaKHWPnGsEMLKSvPfNDdhVQj6t5UX0thv/8e0B/CNvv+J7cpEx1EhRnnTjgZrG2yxKkwKT28wOL7iIW8WEdzG3BccmHkLEhh/Zd/yswpN9bX50TgZbzHD5+WpX3M/HVZBaunQpJkyYgClTpqCwsBDdu3fHwIEDcfAg2alfUVERBg0ahO7du6OwsBCTJ0/Gk08+iWXLlvnD5OXlYeTIkcjKysLWrVuRlZWFESNGYOPGjdTpnjt3DgUFBZg6dSoKCgrw0Ucf4ccff8TQoUMVeRozZgyKi4v9f2+99RbjUuKDk4MqCasDmvl71STNz3Zi3o5En8wZX5k6PKAFrbC07XCwXxwzq3A3Y2b7YeonO5TxEE7tqUVNpTFUHKhlU+qmFhvmUzMdn9NjGg2SpNza8/mMCTy0CzAzWjuyoGcOM57srVbh/hPncP8731qMxTpcBalZs2Zh1KhRGD16NNq3b4+cnBykpKTgzTffJIafN28eWrZsiZycHLRv3x6jR4/Go48+ipdfftkfJicnB/369UN2djbatWuH7Oxs9OnTBzk5OdTpxsfHIzc3FyNGjMD111+PW2+9Fa+//jry8/MVQl79+vWRlJTk/4uPj2dfUDZA3j83PhgxUTubGHXl6d775gbsLTWu5aC8S1UT0/IQR+mi7ExVkNZnZ3FF0ABsRjNHq+K/a856nDhjj28oVrKoI4IeoTzNbKOolQHNdphpdOLirpFymdBE+7osSuWddUVE57BUApYvWHhftfMY5JXJw06WFhY2UpuK+HiLNwI3Qaqqqgr5+fno379/0Pf9+/fHhg0biM/k5eUpwg8YMACbN29GdXW1Zpi6OM2kCwDl5eXw+Xy48sorg75fvHgxEhIScMMNN+Dpp5/G6dPak3dlZSUqKiqC/pxAaaxJ95yeoGRm4Gejbg7++FPZWTz+gQmbBRNDm6nOTjQ2ZxS3CjUBUuKv5+Vh3tqfNMOznPqKyy/7wXFq0lv6Hd1Fs1rvTZN1Vq4Var/juLXnYWNzpeG8ErX3c9MFumYELtIYRat1IfmsCoxv9MLNKC7Xtlm019jctqS4EsUr4rKyMtTU1CAxMTHo+8TERJSUkD2VlpSUEMNfvHgRZWVlaN68uWqYujjNpHvhwgX86U9/wgMPPIBGjRr5v3/wwQeRmpqKpKQkbN++HdnZ2di6dStyc9WP98+YMQPPPfec6u92oezAdMOqnqBhpuGTjc2NReSD8g3MeMi2a4wlvR3rVbscefR6bhz00BpQ3agxCPSHxGoyvXRJWZdm35UkNLM8Gcm1felEzXrLnGTjqXg9F7Q5XSTy6U0e+OCjavfHT5OdzF6Oxz68UIU0cBOk6pAPHpKk9PSqF17+PU2ctOlWV1fjvvvuw6VLlzB37tyg38aMGeP/d1paGtq2bYuMjAwUFBSgS5cuxPxnZ2dj0qRJ/s8VFRVISUkhhuUJL1sgkjhmxwrQtI2Uexan3PMSoaEuNKWJs5IZTsxjcFfcVz8cQ4fmjfQDgk44URtbaJxK0ixvPt9WjDvTknTDESK3DdY2kDQaddrX49HvaMcj2n7Hzbu9iZOiVjRShh91wwqMAdwEqYSEBERGRiq0QKWlpQptUR1JSUnE8FFRUWjatKlmmLo4jaRbXV2NESNGoKioCKtXrw7SRpHo0qULoqOjsWfPHlVBKjY2FrGxsZrxsECv+SkPMrDpqaR2z+PQBGmbwowwII/HzKqdmXbDTVIdKCYilQAkwSHoQmmOr/mWznYlDYu+PYj9ZXRXDhEdKpqUUIhzBkVUv1tcgJfuvVE7HphznkuMh0E/cwtOHi4BDGztMSpA8kk+bZsowgPM0N3hYJeUo3CzkYqJiUF6erpiGyw3NxfdunUjPpOZmakIv3LlSmRkZCA6OlozTF2ctOnWCVF79uzBqlWr/IKaFjt27EB1dTWaN2+uG9ZpeHk9ZrFlZWZws+LbJChtB8dVo2lf86fPDIVnbdugFh/pPdxkl0LD+r1lVOEuScqreGhHf+WWDvm4umLHinCqi5RfeRilsbn59mB0G82swKJuOC/XSBHKzudcfzZi+0RnUmEcs/Ub+BjpPViNtTTYaY/FE65be5MmTUJWVhYyMjKQmZmJt99+GwcPHsTYsWMB1G6DHTlyBAsXLgQAjB07FnPmzMGkSZMwZswY5OXlYf78+fjwww/9cY4fPx49evTAzJkzcffdd+OTTz7BqlWrsH79eup0L168iOHDh6OgoAD//e9/UVNT49dgNWnSBDExMdi3bx8WL16MQYMGISEhATt37sRTTz2Fzp0747bbbuNZbIyQH/tnpJOi2MLQY+yifJSpXAarnix5INVDPiCzGnfNOLzkvrVnYEyiOl5u4VlWmC0zVkb8pEWCaWNzn/JhtXyShCv/byplQtpKNFN+A19bh5kBGjAarGql9RZ+Xp1uSQsMslb/cjjzbd74M2T/cuwEcN5+pNwCV0Fq5MiROHHiBKZPn47i4mKkpaVhxYoVaNWqFQCguLg4yN1AamoqVqxYgYkTJ+KNN95AcnIyZs+ejXvvvdcfplu3bliyZAmeeeYZTJ06FW3atMHSpUvRtWtX6nQPHz6MTz/9FABw0003BeX566+/Rq9evRATE4OvvvoKr732Gs6cOYOUlBQMHjwYzz77LCIjI3kVGTPkAxtt59Rt+MS0tCOv9aVy+clvGVwBUpsX/V6oEKQc1Jzw3mZgPSipxUeqb65v5uBgy3I7lnb1b3IHUNG+zLaHU+eqgy4JpykC1v1KaWyuDGPnqUSzEE/qEu1M+aTvg0+zHdzy16/w/wZcH/yMjcXq/hqkg7ux+bhx4zBu3DjibwsWLFB817NnTxQUFGjGOXz4cAwfPtx0utdcc41ux09JScHatWs1w7gZ+fuxWnk4tYIgndqjQWkjZT0vM7/YhQaxxoVp3g54WU8sRrb2ZCGY5sMsgdoesxPVJUnfz45EOJlFQoKkKBqi0ER5r5z8lby0ba0bH0Uboinzizr3fvKmtm3oZzSw/LYePoXTF8xdzUUzAsjz87cvdwd9ttPYPFQ0UuKuPY+iNzzQDLJGPewC5MnaFiNqE6dPAH5G938meK7Wg7c2TKs8zCRtRCPltvGQnfsDcjxmJgBSVKRJy7xGyvgzNOT+cEzXaz7rU3vKmxnoyklOtxdXY+VOstsbPbTaEO3rSpDI8WicUvzx2BkMnr0eRqGtb71w9mqk3DZymIO7RkrgDPIJQJLYDKx2ndpTpEv5nRyFZs6mBSp5C9SetGnYVVKB6xKvYBZfqNziLodlndFMqIDKAodG40VhoK3+rPpvgf65VJ/n7UfKggX0+CVbrGXGCiaL5eDPdKdKeWBnX65mcdWECxCClEcx2tRJWgQzKlzSeGaPHym67Q45LIzNy88bV7OT8+YeSWrFthKs2Ba8UpefglI1hGYklHsB3jZS5JN82qX71a5S4qXITm7tsV4kKE7tEcJ4QXiXQMinjrG5tbRkSRGEcn0/UpazQs3b31h3Z+IGhCAVAjz+gdKmjOpUlontMtLgRRpEWXu+Ntu55XlT26rR4vXVe5lcCOwmjRQJ2pNSRGNzBqeOiHkyKXyOX7IFR05pX4VBwyXZQQnA/HbEJYIESutbSr7omfrJDkT4gvu5wtjcVC7NwXoxJW9jXj0mT+9HynpatMKYmQNFvDhwwjnNG0uEjVQI8N/vi5VfUpzaYzU4kQZR1qtjs9dryAUgatsG2Qu8xWDlpLezY9RvFG9UHT+CYIPHMx8mnjG6NaJuD2Yi8bo4ZZ8pd/ao4iKxbo/M15SNMyLr+pfHx1tLwkurTlwIEL5iopGiPZltYrFsBsmk6vrwSe8JV0KQClGUW1oEA2EfDKuKaP0jKd0OGEpGmS4hbRrNwPnqGlP54KE9cptncz3UBG3SewR+9+7/ilCmc5+XEewotbo3PV15Meh7okNOGWr521t6RhHXv/MPB31HbWxO0U2/P1wui8c+SYq/+wNzxua0GO3vtO9LkiVI220sSq9WeypLy0Q81oTWyw/nrNqDs7L+RMMfl22zkgFHEFt7IQrVqT0z8VKuplhPfma2IUnQ331l7Q2IFlKcJQLmWkAY0DYGfLdiW4lSO+JyfD7yha/q7UC/8VVcCJ5EJACbioJ9qNG2a7efbjLb9r7aVYr/fn9U8X7y4/8SqedqaEyNYrS/7yo5jY8KDuuGM6sBNwP9IlE74B7ZAsAsr321B62a1jf8XOHBk0zStxOhkQpRzlXJNDGkQCYkke8Pn1J8R4rbDu2LmalFvmpXQ2ikapFP/ACIFS7/6vQF4ytREnYJEBE+8kRUQzCNM38dCkkrrGJsrriE3Xh6dpoVWWnZj39QqPhu3/GzQZ9J/ZHl61Wb8Dc16Z9bdcPQLkTMDA35B4IFjksSXcvUS4tkt1RjckDkYQP12qo9zOO0ihCkvIrBUVKSJIXdiDyGyos10ONYhXLLhmx8HPzZ+qDuo/Ito8eOoxVU4Zy+7NQMrPPs8/kUWhVAf2vPi/jgU30vvVb24N+/RenpC7ppEIUBWo2UGUHK+COmuSRJyNt3glv8vJvXO+v4nB4jOWslCTxstvYo82Qi7g83HdQPZBOvrvrR6SwoEIJUmCAB+H///j7oO/leeJfpuborCBqhSU5ltfETb7uPnQ76zGpyoZ3wrQ7cFwhCKSstjRpaea68eAmnzlUZiq/WHQJ521ZuA8VrorNNoPWpnz69SJyhLn/37U8/44XPftBNQm17XXHCVTemWvQmTls1UhLw9L/0NTSm4yfaePqYtY8V2wgHdhix6ofSoM+kejNzmlgRB0Hol6BccJrZRtxI0kwL/AgbqTCB7Nk8uIOdrarRXXmQVLzbjyi3ywIFlj8s+x53dUqmzGktYxZuDvpMeyeZLiqTpfI7M5FfpvqiMoK5a/YqvmM52ell+abpuYbjJA76kqQwynbbqT0zaZA1UsDvF2tfWQUAJ87qC6lEj/DEBYJyn9GM9tUHH36myBcL1BYo+46zsbfh7TrE7NaVHmo2pfJFFYvUJUlStEMzC1+ncXn2iAiNVJhAtM8ghNMbUEi/byMIUvLk/rP1qGa8ehAdF5qYXGgHFh5bVUcZ+DXSgs8A6Vx52QlBdgFQ297lQuMvTwR9onl/UgiyQ0691Ojw+fhqiQJRe/0Ne+kOHehqliQJF2UGaz4fcJzR6dAaG90fkMZiVu4P5Ic8iFpWjqKKU+6+nLyMHhCCVNhAHMRNaHlYnQwxipm8kqA9YehFsYD19oSPYJcG0E8ObkJv8ojwqdtIUcVPEYxURsSj5gRfH2YnqM0HnN2SYeaTCLWa7aC4AfyVYkuV6k5OgsTBy25JZ6eYaVogbfdx7KpODQNOOzsWglSYQLO1V/uldjyklRt5smWLWd86ctS2qmi+4wHLZEiaQSv4VO2G6L7zEmpbe7TvRROOvLXHbwmvFrXclxVAtzWphdX+onc6U5KAwoOngp/x+fD17lLyA0Fx68NNI0U5trAQBGjjZfWq5MWTMwOB0xpxIUiFCWpbe0YduJG29og2RozvovT5fDhbFbzFIh98x/4jXzce0sqT5DTOar/04qk/EmTtEyGcx1+3ViOl/J73XXtqeaH5Th/yMyRbvd+8t8lE/JfhXf9W6oHqTk5Od+eScs1ru01NaPupTO5KwnhapLjX/HicEM5w1EwQgpTAFqi39nQGHaIgRUyPfcMeNndD0Gd5Vr/YEXwJLwlSh1teeETxndWtKqdVzSyo1dIov7fDAas/XrvKUeWEIv2Rcv2AtHGx2saufU75ZCQhAasnStVejXwTgjK0nm2m+olH/bzRlB2viZj8rkqpjY1GipQ+4TsTcZPiKT6ldPnh1LDn9EJOCFJhAnkgMj48kwY8XqpqPcwZmyu/I2vZzOQoMB26CHgaZ8ZEWeveau4P7N4K5bn95U8D1o6l0/QlK+Vm6tSeyiM8LgBWew/aMaaK5Pk0ACuti+Z1yS4urEMqFlJaLGwMqdsXo1fl1S3NFIUQpAS2QFoxky791esctEIHa+NjYl5NxGPXqT077Mb0iI201r3VioCH4Ok0ERHGjM0V9z7SNEZKjQGr+UktHh7aYiP1b26iJNmX0T1LJeQS2vR/t1o/vEFcuBG8qLOoEXrtsYmtPZIfL1I4sbUnCGlUNFLKi4C1IRqbE8KxXuCR3R8Yj4d2YLGafZ4rQVqiLWqkJJDfo5qoPXC3JLVTx6O9lh8pGqhOhlEKaj6fsrU7daycFiMLJ1ZbS4CPLi6KsiONa5OXW788lzS28NJIkbcRleFYjc3EbVthbC4IZXjaSLFa9WjByrM5Of/KcHZppM5X6V/LY5boSGuzrySRjXArL/Kx8VDPh/XI75HZ18mpvbRY+T311hvFbE22JSTFpcTMdpzPZ58AZqSGzNQn2bM53bNEFxMyeDnkJPUfXhpd2vZrzthc+R2pzTslzzi9jBOClEcxOj7SHr3W84RMHHBoZwgLkN3tsLGRInX+owRDSmPp0A1gPK9esGojpXYJKumCV89v7fkMaIxMaketuFdgKQ/RpEkjfMjjpBWQ2Gmk6MKa3dpjAanOSRopXu4PWAltxGeIGilnYH1K3CjiipgwgZUthlPG5iShz9TWHvHUofK7Zz62ptbnYXdllBjLNlIScXKUe5gG+Kn0H37X2rF8elTcHzBsyGp3+SkmflZtXTIv4JKuqdFOi86WDDA5kZPiVvlh/Z7gY/lOGpuTIAvU1tOnPkhjOaVa3LTbLLb2BLZAu7WnB7XTN9Zbe5Tf6UHrUPTEGfYOCnn5qlEjJirS0vNqEzHphJXXNVI+H1loUptfl353KOgz2W5MBmXbM7PlTplc7fcUz5rSSNGGNTE2qE2UpLim/Wcns/itQtRIETS623Vs+MymRbbVZLO1Sgzn0EAgBCmBLZCvp2Dj/oCsfTEctXEY5Z+opbKYfztOMuphdWtP+uU/OaStPacHMquo+SRSs/9bvSvYo/a3P+lv0arZ4q0heOc2egiEDLn+aDC6bS5BqVlTDctoa4ml/Rc3GymilkgpdOtdFk8DrX8uM6/qgrMzmjjtt08IUmECrVGrHtTG5qwnVkZOCkn5J59EtJZ/p3xrBRJj0dj8kkTOczXB2Nzr+FRspEjNOIrki4MC4g0AAKZ+siM4L4R0TflMu2RBoDehkbIbtbsg5ZyjONDBq2+SxhvyqT3raZHioL2Jwus4fZOEEKTCBUYrOto7qWyQozif2jMet97zdnf2aCY2UsrvSVt7XtdIqV1aTGrvkUb3vX6B9qADqxOq5vVRZrf26FIz01ZIWmO3u4QAjBiA87GRYnULAfEZNruGTHB6+BGCVJigNsgZbYC02x+lp62depNDWpGb2Zqk1Z4dP11pOG79dCxFaRjrghS53ZDsgU6dq7aUltMYuQ7HvCBF1/aIpwJNpCdJIE92FM+a2dqjxdTWkvFHXAG1RopBWmShTRmO1dYq2f+esJESeAijMoSazeFrX+2xnBdS3P/vX99bjlcPZlt7HPT6pJNtdm/tWfUjdUmSiHmurFa+23MmDHzdRK0fKfuFX+KWOyONlJX2dr7amH8zI2mVnzcudKudOna7gEU8wEBpHmEU2nv9Tp2zdpBGOw/cotZE2EgJbIGnsSBpFSK/cdwqpItWeW7tNWsYazxynTjttk2wqpG6JIHYcC5c5OdE1ClqbaSU37Oc9Oj9VCkxo321Uzugtg1MyvXba/cZj19Vo+5uUYqkfeJlI0U0bCdEPHv1XkPxRqj4mWB0IJAJTrcDIUh5FMNbcoTvWKlD7VgNRBC2U9g55GSvar9IWAna3dVJZWYEtSPtPL2xO4WasTlpIjLb3m2feAzYLVlOSqWtkKAx/pZDKnM7LrO2Cqn9kNuU9XoipsXgXEhkBNnHGgmnxBmn5WkhSIUJPG127GjEROUKM40Ue+NP2nR4snm/Na/pkiQRNTIXCFt7XscHtUuLlWHNtg1aGyySgGDKrkXlOR7ihxH3B6bkH6dnSpOQ+g/p0mIWEgjtNqJR1ARWUszbj5RbTs8MIW8jNXfuXKSmpiIuLg7p6elYt26dZvi1a9ciPT0dcXFxaN26NebNm6cIs2zZMnTo0AGxsbHo0KEDli9fbjhdSZIwbdo0JCcno169eujVqxd27Ag+hlxZWYknnngCCQkJaNCgAYYOHYrDhw+bKAXnoTUSNxc3/0ZM2tpgZSPFww8W0deSzRv5JMd/RlCzkQrVrT1aVwEst/ZobaTMOrG0q8UZKRJWxua1dwm6WytFa2zORCNF6drFKJEG7AcXbNhvOT0zhLSN1NKlSzFhwgRMmTIFhYWF6N69OwYOHIiDB8nOx4qKijBo0CB0794dhYWFmDx5Mp588kksW7bMHyYvLw8jR45EVlYWtm7diqysLIwYMQIbN240lO5LL72EWbNmYc6cOfjuu++QlJSEfv364fTp0/4wEyZMwPLly7FkyRKsX78eZ86cwZAhQ1BT472JhKewY8dqgCRImUmVVtXOo7zsXjRZ3dq7FEZbexdrJGobJqYe6olbVspDIKxOWvHCyETG6tJcwF3XlJAgH27hcxCFJKCxOEgT4SOPA077bgokpDVSs2bNwqhRozB69Gi0b98eOTk5SElJwZtvvkkMP2/ePLRs2RI5OTlo3749Ro8ejUcffRQvv/yyP0xOTg769euH7OxstGvXDtnZ2ejTpw9ycnKo05UkCTk5OZgyZQqGDRuGtLQ0vP/++zh37hw++OADAEB5eTnmz5+PV155BX379kXnzp2xaNEibNu2DatWreJXaJQYXYjx2pcH7BmwSTLBfhMG7bRezHm8ktOd3Si1W0PKPFeGoEaqXkwktT8x0xopSk2EDz6F+w0zKarVHw8tjqTma4EY1nj85C1Q4/HYDbWxOYMRh9eJZLUFmdNaoECcHlq5CVJVVVXIz89H//79g77v378/NmzYQHwmLy9PEX7AgAHYvHkzqqurNcPUxUmTblFREUpKSoLCxMbGomfPnv4w+fn5qK6uDgqTnJyMtLQ01fwDtduBFRUVQX9ugHw1CqO4bWjFJN89Zk4ynTirPPprl88nuwceq1q1SyonsULRRkqSVDRSDE9YEVf1RCGezaLH1q090DsXNTO5u2jONgStQ05uGikGA1mEj+xB3m5TBS1C9tReWVkZampqkJiYGPR9YmIiSkpKiM+UlJQQw1+8eBFlZWWaYeripEm37v96YWJiYtC4cWPq/APAjBkzEB8f7/9LSUlRDWsnaneGMYnbhg5FdFLIaEVq1zUKdqvCra5G1YSLCwZ9DHmBfcfPEi+qpr4IloKzlRfp4ifJqWZVUqSvuWxb08fJamvPB5/rtVL0V8RYrxNqw3aDqFkIkN7DKZzOCndjc7kaWZIkTdUyKbz8e5o4WYWRoxcmOzsb5eXl/r9Dhw6phrUT0jFYVo2PQV/VhSSEmNFIkSBf58Ieuzu7VUFqxbYSzPh8l+J7o84avcKYhZsV37Hc2nvrm58U35G1VKRFj3E+21Zsm8sFSQJOEwRFomdtM/ET+785Fyh2Qrvd5maNFECuM5Ktl1M4bTbBTZBKSEhAZGSkQntTWlqq0ATVkZSURAwfFRWFpk2baoapi5Mm3aSkJADQDVNVVYWTJ09S5x+o3SJs1KhR0J8bIGqNWAlSNnQong4u7fJobbf6mZfgFooaKTV4Xz5NPhVIF84sPCadSxJQRbjMmna7VA9SliMjfK4yeCZh5117pHGYhY3UJYmcPzdppELWRiomJgbp6enIzc0N+j43NxfdunUjPpOZmakIv3LlSmRkZCA6OlozTF2cNOmmpqYiKSkpKExVVRXWrl3rD5Oeno7o6OigMMXFxdi+fbtq/t0MT2NzHlesyCFuMREGbjPQTgBWsbuzk5yCsiAUbaTUINtIsatIehspZklyEbCNeB43t7VH1tK5aTInQdLI8dJIkXYGWIzN5eersW5PmTJuO7YiKHFaIxXFM/JJkyYhKysLGRkZyMzMxNtvv42DBw9i7NixAGq3wY4cOYKFCxcCAMaOHYs5c+Zg0qRJGDNmDPLy8jB//nx8+OGH/jjHjx+PHj16YObMmbj77rvxySefYNWqVVi/fj11uj6fDxMmTMALL7yAtm3bom3btnjhhRdQv359PPDAAwCA+Ph4jBo1Ck899RSaNm2KJk2a4Omnn0bHjh3Rt29fnsVGhVGV9j83K7cYWTW9fcfZXgdDgtRPGsRG4mcGSW8+cFLxHY+Oafegz0tRGE4aqffzDii+Y3m44qtdpYrvjlUoL8xmlWSEigd3q2zYd4L4PSuhgZhlyXlNhB4/n1XWJa9xgHy/J78CcpMQ6/RJYq6C1MiRI3HixAlMnz4dxcXFSEtLw4oVK9CqVSsAtRqeQN9OqampWLFiBSZOnIg33ngDycnJmD17Nu69915/mG7dumHJkiV45plnMHXqVLRp0wZLly5F165dqdMFgD/84Q84f/48xo0bh5MnT6Jr165YuXIlGjZs6A/z6quvIioqCiNGjMD58+fRp08fLFiwAJGRkTyLjQuFB08pvmPVyfaWnmESjxY8/fkc/PkcIT02cTsJr9OUZ6uUtjDhhBOmISy3sHg0iw82kn0DFpdfIKRvPAN/X1+k+I40JkRG+GzRkNPy8sofFd9Vs7i3hQBJs27VKa8WLMr5o3HdMGyu+il4Wv7w7+/x1VO9LMdjFp/k9LnBEKeiogLx8fEoLy9nai/1wcaDmLx8m6U4bkq5ElsOnWKTIQdIjo/DUcJAzYLoSB/RO7lA0C6pIXaVnNYPyJDfdLuGmdfouOgIR7dn72jXDKsJmjijtGpaHwdOBC+CYqMiUMloy58Xdo4tt1zTBJssXhWlRsO4KJy+YH5R1TAuCt9N6Yt2U7/wf3dr6yb49idz+d3/4mDTeVGDdv4Wd+2FMW6RoW+5pomp54xqXKIjfZh+9w1UYV20qLWFuzolO5b2o7elOpa2GZywx9Drq9cnNtT8PRCnbdxYaYxYOelcObEHg9zQY+cCjaePPytClNrzSx7LxMJHbzEV38afyNvLdiAEKY/CQtXvFllhQFqSqeeMasgf7NoKD2deQxm3sdIZcmNzY5lxGWWnlbYcvLimaf2gz3earH+n+PGY8a1snw/4528zTaep1xr7dUjEnTd4oxx53qhA0213/eXOoM/XJTbE/xtwPZM8uQ03bXPSYtarzci3v2WbEQMIQSqMMTOg8VCfkowkadDL/2v33RT0+Xe92phKh4aWTYKFg+3PDeCWFg/yfjqBzi2vVHzfrU1T5mntl23HnDqndITJm5Qm9YI+739xMJe2Xcfs+zrjltQmpoUdva6amtAA9WMu224a0VAZ5bmhdFpdNVgpSQ6fPK/4jmQnJCcuWmnjSro5IRTYedQdN2uoQRKaWPkHtBMhSHkUFo7ojA5o7ZL4DM67jwXbm+x/cbCqN91A9FZbURHBzTsuit8hAflAfEUs13McXAicfOPrRWP/i4PxwZhbuacbHWX/MDRrxE22ptepxZUAgBiT76qngb69bULQ59ZXNcDevw5Ewzj27XD/CWtHZfX6bXfZu9jB4I7e1iirUcXAsH3/i4Oxczr7hWHOyJuI35uVo7oQFoJ2IQSpEOSxHq2pwh05pVzRaTHqdj62LFsJBu8NKAQRPcd+UZHBPTI2ml9z9+IqSk7gK7S5qgG3dCb2vS7oc/dr7Z84eWsg5NtHJ3/RupltJno7NImN4oI+d2jeCFGREVw0iu/9b7+l5/WEwltbs8+zHiQtlZvhqT1944Euiu94jG/x9aKDFAJP968dF8wqCf491jn/jkKQCkFSZNtMw9NbYNWknnjyjmuDvj91rtpQvPMJR5ALp/ajNuBW4+gp5cm7KIqJTs+QMlomSMVEKpv7d1PY+AQLHGhGZijvV9z3wiCs/2NvJmnxIrA4B6bxW6EP63J10OcoQr3Yya2tyYcdrNjNxMo0Tz9rbF+2DhBaO7WIx+RB7RRhjGqP2zS7AgCw/Qj7rZ2rrwzeFv1uSl98/PvbUDC1H9XzekJh++b8tiXV4CFX75w+AP8ea94uzijx9aKZxNPx6ngm8eghQQpaWNz5y5hjtC4+HHMrimYMQoSD27NCkApB5Kfg/p1/GNf+MrBaoUNz5fHPxg1iqA241RhHsF0aTGG8rbdF8ENx8JYhqaNd1TAWRTMG6aalR+CA8MKwjorfIyN8aNG4vuJ7t3DbtcFagPj6bAZlEm5b/f9teCfi97/vfS32vzgYD93a0nCc8vs4O6dcqQjz0vAb8dMLg/D/+gcIbD4fHuvRBjdf01gW2pgkNfAXA3650MqCZ+/qEPS5YVwUbiK8nxqVOg5d05KDJ/L7b2mJ+28xXgc01Nl78dC41I+JQobJE8lyFo3qqvn79YkNsfXZ/kzSIsGjfKJVFlB6990q4/EZfoY1QpDyKFrq8VayU1FWjUPraM1pu2fkzUoNzo2/2JRooWdsvmY3na8a1p2Q1bbR472DNYg8F1zx9aKDhMF7OpMn4PV/7I0X7lEKikYwaycEaJ+O7H39VabilGtw5bCwRyRNGiMyUlRX0Y3iggVZoxqpujb9K5V6tMJRmUmAXPtWh9piaOvhcs34oyMjgrQrB38+ixnDOiKOw9Z8XZtnISjw3G6Ta9flDLhB/f5Xo5CKQv7dk33a4j7CuG2Em1WETKPjnBs8rAtBKgSRb2GlXW3eEWiggfnwdGsdRw3SxErTl/Q60NCb2E8idtKicfAWSvbA9qphnxms/hsNK7YFX+Cttlps0bg+HuhqTTtA2mKlpUmDGNXfbm9rTpDSg4WcTWPzB1wWnuVpUglSpAlQ9nn/i4N1tRt6/FQWbGxeJ7TJ03rjgS6mhIvoqIggoalts9ox6Pok9hfA15Wrz6aZMHdiD+Rl32H4Ob3t75ZN2Sxy5T7dRmS0AKCs20n9rsOL995oOT1S1zK6sG3WMNZyPqwiBKkQRL7KveqKOJWQ+gRqV5Lig+MZysiJY+AgQdrmA8irPb3JRe8kTr8O7FZxPJBrthprCBGdDGytkFBuJfFDb3Wt/ezltiLXkF59JX0718tBwhXqZW0FvXTV2iRLJ6AdWwRvnc17KN3Q86kJ+pP2J7+/zVCcgURF+IJOvQ76pR//Or1FULhPH78NH4y2JhTWIa+Xz568nUm8cmKjItE8vp5+QBl6fYbVbsHO4mBt4bRfdjNYae1ptIpGk4p1gamAEKQ8ipHthiYmJ4XxfdpqNmpWO2INAvzfaBlM/pbyNGIdep2W11alHLkDSloCBSm17ZM6aPzn0KalxqCObBw+BqbV4zrzWqRIWQO04/Jsp9ASo4wKffJJ+c60JEPbrWpbMoE0NyDUyomNigiauOtOkMoPoNzY4kokxptPJ5DArb1f3ZRMtAdlgfwkMS1nAryAkwRf0rg5qd91iu/0+Pann4PGdb/GznBMZAJPlyptJSVTaVnRcLPC+RwIuBMoqBghKsLHxD5Ej8BBUyJ8V0ezRsYGzViTfqP2vzhY4bBRTuBJxVG3pxoupXoUq6hAgUOuBZDLPZ1bXolMg8fG+7Zv5v93l5b6Gqn6MWx8EgXWrdFy+2TLEf+///KrtKDf9pexE6TUdo2fkJ18tYsfj/G9289IPQRu9/PQ3Mn7ftMr1LduWI1OgYLUpH7Xw+fzYZgF+zI1DRLNaWQSgSeUSUJeK4Kd3303pxjeWpWPe3XFElglZk9pp7dSjjGkcd6ovRpPtza0OJ8DgSmMXBFjVi0bFRnBTOtklMBk1/3BnNsAXS2LRhF+MFrbEWWgBmjyoPaGr9t58V59g+1Ah6KXJCmoTDZODnbbEB0ZgesSjZ3MDBQ0rW4NmsVouZWfv+yyg6e/ocC77QLL/ck+bbmlGUxw2/1e00CbrpMu+13mL6GV4Y30c6fdVQTCasspMJq6bVQrx+mvbUZ24dCIoDmi0QYG9lXS2F9XJ4ECXDVDI+zAcu5EcRCIRHSk3rL8F1s7g8UuNFICJvCy9am4UG14xXdvlxb6gQyid6qKB3pCWKDNil5YteHs3d9kaD5XP/by4FlzKXj4vEpmYBkdGWF4UgncZuh9fTONkO7hdg3nnSyFfrU6i46MsGSXw+eYtvqEGZjeDTK3AoEkX2ncbkcT5w9SUVEnMJOqpZfJU6BakFx/7KC4TipwkaRlLhe4+JL7+6Lh2SHB2ibyfYbmKndj0c86Ieq29gxqpBy4GUGO8zkQWCZQXWzWHofEp1uOas5OpP7EU81qp3KsVOcSX7lNgpm83dFOWwAOHCB4XD4aOOhacUnAEr2tIjUtVNtmVxgagPUEGi2v+d0c8MTOksBXrzuQ8Ztu13BPN4OwtWMWua88APj32EwMT2e3kDMjiNRhZDyIjozQddYbqB1jefBATp/2zXT7htnUSdkmn9q7/O95Dym9rCvDO+tDChCCVEgQqBHRbOQBDe7GFuqr0zoezmzFXXhRU+bY0Te0yqrmkrbxNisvwloEqvNrZFt7LLByeo4XbVW2ROpQ05z4fMbajKQzGelNFjckszNGNtPWv83uo4xHb+OE8PPTv3hv11vVX8nAQSuNU+BGlHcDvvzrWieqga/UsUW8/3tatCZhK76laIWNugVM4/raC4jAvLAUo+TadJ/Pp983TApytP71Aou9LcfLt1kiBCmPEjho/lB8+RoIzTYe8OOEvvq2HjuLK7g6gdTCqUXGmO6pv6SvnYF6jAyvtQic3HTkOlPYdeP9aIZ3NGoZ6zJtMwH9iNQWtE5JGnVUaGZeChbkzb+4z/9/c3FIQeWkHbaegUMvepqKlow07/6tPUKKdu5O6gltgb+yVEiZWUyZVY53b5tApT0KrAuvXP4uBCmPEmgxU1yuvKtODxqDwT7tE02pTc1cqSGHo/Y6IA31RBIaaDt5s0MGOfTzOf+/aa7gMFpVSqebfF7qvluMCRZa76FlADzkRnq/ZrpbezoNcE/pGdXfrLh0qEOvLoOFYAadRSc99+kuzcHr4nU5RstLr76DNFIMB8eYyAiFmxgr295a/OqmqxV51/Oi3pBSQ+k0QpAKAeSO6lQJaKFaR4rrMOtw85nBHfQDqaA1RhgRFGi2LrXSkhtzK/JiYKg0O+61CvBWfHtbO+xy+EivaieY1Hj9/s6qv8l9RwVS36SbDxJWTNI0tWbmo6VOww2Qis+YDZv5tCf2Vfef9Ic79S+i9rtgMZCm3MaMuvnU+WnSE2QDfteK22i5VVy4aGgBope+FnffRJdOoNAYHRlh68XPZhGCVAgQ6NlV0y2CbEb/v9uu0Y1ba7xWSykuOhKLLXoctrpNY3XR5gL7RVyTcHn7wqiBKY1W0A3vKEeCpDnhau5cM86HmwnWzFHanjisV5Ig4WMdj+csSr1xAzb2i4F52TZN+0Jgqyenjdi3aQ0FZsY9rcUJKTrSWJTYSLnwTGwUi/sDtNE+n/blwlfE1tabfM5hdfEzT4Qg5VGqA2w05JeI0vLsXfqO1YwOvnV9rMTEdqObYClkmI0r6BCBwQHyse7kq3a0sX+iJW1TaAnvZp3LBkIy1JZjRRA3+qj1tqbh/oBLeua5KeVKvPebm5nFR9waYhb7ZRrGRRvy7G80D3oaxmBjc7ZCfoRRKYCQPOkexNrDMnoCog+z7++MF4d19F9B5sYFnh5CkPIoNQGN+b/fF9M9ZKaFajyiFVvhoZPG02KI1c7IcvVudlIOdE9g1C6C1arcCbSvJbK+bUZjd+FufRQZM23e6nsaeb6uCWudeNQyftfrk2b6WZNfTBxoBLI596sfxZenbTQres4/AwUprYMn5sY9Y32KtO1N8qweFeGjys/QTsm475ZADbqP8C93IwQpj8LS4DAQuYpaqyET7SB+eWB3CfsrLQLzckc7bQeSNMXD0taAxyoqcGw1arPTMC4aTTUuOSZRZxPXmuJS2kAmD2pnKLweej68WKBXXVb6l+ajHGcG2vvh7Nji0yqDGo0ftbdulb8S34WiM86+vzMezmzl96NFU91WPJ2rQatdCj5awFgjZdB8g5Q+6QRwZIS5lhYYlVcWNEKQ8ig8HDSSMCog1A1I1TV0+ZOHuiLWvpu8rcii8nLR8itlVsgK1L7Q2EjJh638qf0Mhc9s0xRfPdUTnz3Z3UAugcd6KLcR/zzE/IGDlTuOEb+PiWJzZZHPBzTVcfx5TYChPylNVhc4syQrsxWyB7bDf5+4nfg7WRAJ/r8aRo+tk+Oo/X8TgwK+FlrvpMXQTsmYfneaJRcgauVMmwcj0NpImUHuekEv77RzT3H5BUXfoSmXoLtXdZIamOaOfigEKY+ybk+Z/9/PDG7PLR2znZbmUt5Apt99A/q0a4ZfZ9Adlf/7w9rXq9RRp2GjPYFo9n1H3JyCwR2b46V7b2QWZyA0YxeLlWqbq64w5O+nDrlxu1GB5+ZrGgMA7r+lpeazamVptIxbNK6PnJE3Kex1/vP47RiYloR3dNqXWWFgYt/r0Lh+NJ4MuPw4NUHbUeXCR2+hijs6MgK/7dkGaVfrn1itQ5L9HwCKZgyifj6QQO/4pP5fV0c0l4mTt9qsiydqcZgR0NtcpV5vLGWdvhTexq1gdrGsx5nKi4rypnnUyC0L8svcncIbThoECtbvvSxIsfS1QdOn0ls1Rv6Bk5qOB18Y1hG9X15D/G3KoPb464ofgtJ7OPMaPJx5DXU+9dTsdUJFzsibsG7PcfS8TrkV2LnllarPGx22YqMi8caD+tcZmIXXVi4rBtyQhEXfHvR/Nlp+i0Z3xf6yc7gu8Qos/e6Q5fx0bnklCg+e0gzzq85XK77r2CIebz6Ubjl9NVKa1Ef+M/2C2u/1SQ3xVlY6khrFEZ/p3jYBIzNSsHSz9XKhweykXS8mEq/8uhNqJAnxBjyhf/10L9WxQg+rFzBbwbCRtgHuvyUFH26qre+Hbm0V9JuVK2L2/nUgrp3yedB3co1UUqM4XJd4BaIjI4iHO0j3BaqNT2bq4uor6yHr1laoHxOpK1S5xTBdaKRCgKCbwTX6mNzxGqB/JQOpoS557Fas+0Nv3KZx55hWvGN6tPb/Wy275AEy+Lslj92qmkYdDWKjcGda8yAty9dP98Jr992EITc2J6ShG6VhrmGwanJSjhrWpVbgGNO9tWoYo9qCTr/4+arTQMZGReL6pIbw+XzIP6B+UEGtfmqviLn842MaebWLOv9u/WV2h6RFwIAbktApwOlqkHMDnw8zhys1nSwx2uwf712rUZs2NPjk773pLTBCRausdo8iSavw0vAbUT8m0tIWsRECXQA0phQCgw6DyEYy2vJU69czhl2ub3kQGo2eGlGREXj0ttSg7+R9KiLChy/G98B/Hr89qE/9aWA7DOtyNW5tTXZHQHMFEG25/OVXacgexG+nhTVCIxUCVNcoj3FcfWU9HDl1Hi0DTlM8knkNvvqhFANuuDywN6oXjYoLFwHQO/mLjoxACuGUht3IL7CtHxOJc1U1ALQn9tSEBqoqYVqBhaaklo/rhn98ewB/vNO6MbYESd9pn8HpkFZofOXXnfDXX3XU3PJT2ELoRL70t5n46fhZtG+udNZ58zVNgjSuNMjr7U6GthNmt5T+8qs03JmWhMw25IuWzXJvF/qLefU8R1PHI/v89IDrMaZHa6o7J+c+2AVf7ijBqNvphdsbW1yJbdMG6Now6b3LV0/1xIh5eThxtkozfESED8t+1w2VF2twpc69d3XYdcVSXSpP9bsOx05fwHWJ+gKLFoH+6QDy9TQkYX9sT22XKv/6bSY6/yVXM+4e112Fn8rO2nJXqZ0IjVQIsOXQKcV3H4zpige7tsSiUZcdYzaIjcKy33ULMg4ObOetmtZXDDTZA2tXBXqdqA6jJ77UoFndyKkTogDr9kKBgsBt15qbCDu3bIxZI25CImHL5oZkejsWgG4VysuJpM/n07WbMjqlxEVHokNyI6LApeXF/WqVS4sV+eGs89cWrmrrIS46En3aJ6K+iXsZ+7avXeyQNLsdr6a/MDkwn3XCJs1i4S4Km0LayXBQx+Z47b7Ohm3vWAgqba66Ah9SaK6BWpOFbm2s3SBQd4dpoKbu1ZGdAJBtWZsRblCQ2xvWVdcTfdri+V919Lft9r+c0kwIuKXCTImx6imNKewG/3hnO/zl7huwYryxAy1uRwhSIcDthC22Vk0b4K/3dNS93DPIPwlhgO2UciV2P38n/jRQW6vyz99m4ve92+AR2VUJZkm7Oh5vZ6VjhcETZDywcuWNnPV/7I3l47oRBcWtf77sPblu1fnM4Pbo1qYpRhLs0eqEilgDxpncUGikgj//6pfrIWgm6F7Xq99Vl9KkPhb83826HrJZcs8vtlS07gVYMDy9Bd77v5ux+uleqmH6/OIC5BEN28KUJvXQrU1T9OuQSLRtUUNt+4Y7Bl1HNAvwqB2juDvylyht3Baf0Pc67H7+TtySern87uncAjueG4DRAdvN//xtJm5t3QTv/Z/yIMEtqXQLt78/koGHM1vhXxavUOHh1kGNejGRyMq8hnpBRELPy7wTiK29EEDvXjgtAgWpO9o1w5GTSi/pNNqQW1KbBA0eLDQC/W8I3p7Ri/KuTsn4z9ajAJy1KdKiReP6aNGYLNySDHRHd28dNAAH8v6jt2BW7m483rt2FWzXXWbE+HTSfvHeGzH0pmRkttZf8ZO2GgLpdb22DzFi+sM64k8fbTP8HFBrgP5tdh9VlwkD05Lw+faSgG+sF25EhA+9dd7zjQe7YMfRCs0LrX0+Hz4Yc6vsO8vZcwTSOBcbFYntzw1AhM9egUBO4HhDGi8bxAZPtbekNsGSx6wJQFdfWQ/T704L+i7jmiZY++NxXdvXOq5LvMJSa304sxWWfncoyO41EB5trWGc+7YFuS5lT548iaysLMTHxyM+Ph5ZWVk4deqU5jOSJGHatGlITk5GvXr10KtXL+zYsSMoTGVlJZ544gkkJCSgQYMGGDp0KA4fPmwo7a1bt+L+++9HSkoK6tWrh/bt2+O1114LimP//v3++4EC/7744gtL5cKCOtU/AHRp2dh0PIHtfDjt5ccmULPrMCLwDLkxGTGREf6VuJwHu+rfL2eW1+67yf/vSf2uY6YPNzLQ9LiuVlPT5qra7dNrm12BuQ+mo4OGp2g1bk1taukVWv+Sh+sTa22cAt8jiuCILy46Ene0S6Ta3uExHdJc0q1FUnwcolU0HrNG3BTUPuxyIxgXHYn0Vo0Nb4EFhlZ7NLAGE66IdYXw1eu6qzCuVxu88UDw6dgrYqM0t08D8+6C1+DKrBGd8Hjva/Hp43Q+rqbddYOlRe/0u9Ow47kB/sXhlbLFIG/nr25ZMHMVpB544AFs2bIFX3zxBb744gts2bIFWVlZms+89NJLmDVrFubMmYPvvvsOSUlJ6NevH06fvuwpe8KECVi+fDmWLFmC9evX48yZMxgyZAhqai7byOilnZ+fj6uuugqLFi3Cjh07MGXKFGRnZ2POnDmKPK1atQrFxcX+vzvuuINB6bAjIsKHF+7piCtio/DafZ0NPRvYh9pz2rqYfvcNaB5PPtpthCYNYrD9uQH4+yNkHz+BE53ZsaFuVSt/vHWAr58e112FRg6sihKuiMW2af3x5YQehp/t064Zlv3u8gr4iT7XIpZwipOWf4zqisd6tMZ7/1frhymwvN7KsuY+wMjYWNdmSa4MAlGRgUwT2L7qxUTi7pu002eJ1bkjKjICIzNSMKhjkv8winwyDfzYr0OipZNiWujdUBCIz+fDH+5sh8GE07ZB4eS+i2yYbFkKmlZcnTS9IhZPD7ie+qRwt2sTLOc9KqBzDUzTrptQhdvW3g8//IAvvvgC3377Lbp2rTV4fuedd5CZmYndu3fj+uuvVzwjSRJycnIwZcoUDBs2DADw/vvvIzExER988AF++9vfory8HPPnz8c//vEP9O3bFwCwaNEipKSkYNWqVRgwYABV2o8++mhQ2q1bt0ZeXh4++ugjPP7440G/NW3aFElJ7vCgqsYDXVvivptTDKu3FV5tOSwgBqY1xz/y9jOJi9ZZm9Gx6Mk7rsWygiN4TEVFLdf6pF0dj7E926BFY/N7/WbQUms/dGtLvPu/oiBtZR0+H9A55bLmsl50JB7r3gZrdh+ndlYayNVX1sPkgOPJgRNxj+uuwhIGvqBoWPLYrSg4eBLdr03AjqMVquHsuBbFS8jdKcgn78DSGt+nLR64pSXGfZCPP93J9ki6lgsVN/Nb2TjhFs2IGVguoJWnd5lFTZWeU3ATpPLy8hAfH+8XZADg1ltvRXx8PDZs2EAUpIqKilBSUoL+/S8bk8XGxqJnz57YsGEDfvvb3yI/Px/V1dVBYZKTk5GWloYNGzZgwIABptIGgPLycjRpojSyHDp0KC5cuIC2bdti4sSJGD58uOp7V1ZWorLy8l1hFRXqgztrzNgI2NYQbUgovp755jyp//WY2O86oppbbZDUM8CnwQd2G0Gtr7oCO54bgPoq22eKa23qRxu+DkYNM1dBqMZl4Pv4etF+WyKtcjxfXaPxK1t4T6p2dNnA+kyKj0NSfBzW/YGfJv6G5EbYcbRCV9tkhqCtPUbjkK1yE+fE7rqxOcrPVaGzBROROuSly7utukWA5SZIlZSUoFkzpdq2WbNmKCkpITwB//eJicEr6sTERBw4cMAfJiYmBo0bN1aEqXveTNp5eXn45z//ic8++8z/3RVXXIFZs2bhtttuQ0REBD799FOMHDkS77//Ph566CFiPDNmzMBzzz1H/I0lrOQSPcNeVthhB3ptM6VPIiMEDrJaggFLL+M+n484GphNQm7UqkiLE4oBlENSVkr9ukRrbcNN8Jg7FFt7Nmvw/jGqK9bsLnXV1pBWG75k012nduDz+ZBl4FYJ7biC/816HKizzXQbhi0Hpk2bRjTADvzbvHkzAPLALUmS7oAu/53mGXkYI2nv2LEDd999N/785z+jX7/LF70mJCRg4sSJuOWWW5CRkYHp06dj3LhxeOmll1TzkZ2djfLycv/foUP2bHGYRcs2wlK8ss9yga3OW/a4XnT+qZyEp6zp1NUvrFPlVUZzDVy7o5WFQEGezZ1tGr+5ZLvBCna/Q5MGMRjWpYWpex55cUNyPG5KuZJ4QXXoiFH8eOXXnTQXdqGE4bd8/PHHcd9992mGueaaa/D999/j2DHlLe7Hjx9XaJzqqLNDKikpQfPml1cmpaWl/meSkpJQVVWFkydPBmmlSktL0a1bN38Y2rR37tyJO+64A2PGjMEzzzyj+V5A7Rbh3//+d9XfY2NjERtr7YSQnShVsXxGUHmsM++9EY9kXmPoglUtkhkYs6shScETix2DKO+JjL38xkejEWjvpRejVplpaRtZ45btBiPI/Zrxdmhah5vvkIyM8GH5uG5UZeHet3COezpfjTOVF7Fh7wkuW7ZuwrAglZCQgIQEfQPBzMxMlJeXY9OmTbjlllqnYxs3bkR5eblf4JGTmpqKpKQk5ObmonPn2tNnVVVVWLt2LWbOnAkASE9PR3R0NHJzczFixAgAQHFxMbZv3+7XFNGmvWPHDtxxxx145JFH8Ne//pXq/QsLC4OEPK9j18pTnk50ZETQ3WJWSZIJUlbHZ6WmjpOAyXhrzylYFo9aXHpFckNyPDq1iEfzeOUBANa1Z5egYRc3pVyJNx7ocvkUn8P5sYKmQG04LvITXuufQEC52NR2fT4fGsZF458WHYZ6AW56t/bt2+POO+/EmDFj8NZbbwEAHnvsMQwZMiTI2Ltdu3aYMWMG7rnnHvh8PkyYMAEvvPAC2rZti7Zt2+KFF15A/fr18cADDwAA4uPjMWrUKDz11FNo2rQpmjRpgqeffhodO3b0n+KjSXvHjh3o3bs3+vfvj0mTJvltpyIjI3HVVbX+et5//31ER0ejc+fOiIiIwH/+8x/Mnj3bL9SFAvYJUpz9iXCN3fsoB362JSavXSunGc1OUpERPnz8+9uIbc0uW0AvE6g18HJxOSHkREe6t8DeeTgDU5ZvM+wax5W4dKDnuoG5ePFiPPnkk/4TdkOHDlX4adq9ezfKy8v9n//whz/g/PnzGDduHE6ePImuXbti5cqVaNjwsrHoq6++iqioKIwYMQLnz59Hnz59sGDBAkRGXt5f10v7X//6F44fP47Fixdj8eLF/u9btWqF/fv3+z8///zzOHDgACIjI3Hdddfh3XffVTU09yLyLZgOyY3w2bZipmnQXLhrFTttP724GrUTH4DubRMwZVB7tCNcSmwoLoPOFNUEdjsEg9ZXNcBPx88yv6TYCbwsSMnh0V/r7rX8Xa822HPsDG6lvNbFCfp1SES/DmRzGq8hr0q3DMVcBakmTZpg0aJFmmEU/kt8PkybNg3Tpk1TfSYuLg6vv/46Xn/9ddNp66UBAI888ggeeeQRzTBOwWqckw+Yo7unQpIkU9dwaMXL/RSQrB3d2IKN7VWowN+fi3IrVO3aCP24yN+zGjR5CcIrJ/TAhYuXcAVnA1tbHEx6enNPHVb9oK4O/nindRcooUSoths9wsOkXqCKvNnHRkXi8TvaMk+Ht/uDurll5cQe+M/Wo6qONdmm5p0U7NSiudF+KPBm+ihO2zBRkRG4grULdYdwYRVSY7dTSIFzuKVqhSAV7thmeMg3/jpB4brEhniqP9nhqhtxy0BgFVucRFp49orYKPzn8dsRGeFTvTPPCG62iREEE2gfJz+Baxaepw3lUUuc7Rm9hLzcw2JrT+B+bOlUkg2XV3LsUtck1OcWt13IJw+eGiqWNc0yro4Mt3t/1+tafLWrVPUybq/jRq0iLVfJLqhuc1UD9GnXDFfWjzF1+4NAoIcQpMIcp9wfsIaHYLDjuQG4WCMpbpZnmdbcB7vgsX/k4y9338AuUgL2bu1ZjiHo08OZrbAw7wD+4CJ7lCYNYrD6qV6OpN0wjv+w7WVxo0/7ZhjXqw06/uKjzufzYf5vbmaaBs/uZEf9ehW3aKDkiBrzKLw8kPOCu/sDDj3MDq+8/W9Iwo/PD6S+jNmt8Kze54begDHdWyOlifc1g1Z4/ldpyPvpBH7V+Wqns8IMHv3W5/NxF7rrRbP3wP78r9Kw/Ui5/+5IL2LXwvzX6S3w8ZYjeDizlT0J6iAEqTCHm6NJhadrvti5UmGdlhNCFM/yYt2mfD5f2AtRAPDQra3w0K32TBwe3tnjyl/uvgHLC49gXK9rmcetVrfx9aKZp+V1/vbrTnhhWEcm9o4sEIJUmJNwRYx+IBPERl9u4PViIm3Y2rNPlLIjKTdfnUEiXI89hyp21afXBLaszGuYXfCrx0vDb0RR2Vl0adlYP3CYEDgsukWIAoQgFfY8NzQNZytrmKtI46Ij8e5vMlBzCWgYFy08S4c4vKrXW+KkwCgeWy/YyoiMFKez4Br6tk/Eqh+OYdTtqU5nhYgQpMKcpPg4LBrdlUvcd7S77E23e9va+xnrc7rdPVQG5L7tm2HVD6UY3Z2nHyx3I2Ru5xF1ELrwrFteUb/5UBfsLT2DdknWbkrghRCkPIrXtlJaX3UFvvl/vdGE01YiT/cHdvLmQ+nYX3YW1za7gkl8TRvE4MTZKu5XRLDUOEZHuEdlL+CL/LJxgYBEdGQE2jdv5HQ2VBGClMA2WjblZzBsp0aKp/1SdGQE2iayW3WtnNgD246Uo0fbq4K+Z/0K7ZIa4tbWTXBVQ+sTY0qTehjW5Wo0jI1ylR1EOJGWzPeKpfmPZCD/wEkM7thcP7CAKUNuTMaLn+/C7dcmMI97eHoK3s87gE5hdkWXEKQ8SupVDZzOgqvw8qk9njS9ItbyvYk0RET4sOSxTCZx+Xw+zBpxE5O4BOZo2bQ+PnvydjRpwEeD3Kd9Ivq0D42LdL1GfL1oFE7th0gOzkk7tojHpsl9uLUbtyIEKY/yxB3XorL6Eu5MS3I6K66Al+1VqBIOV5wMubE5/vt9MR66taXTWfEkN3DWSgmcI4qjprdZo/DbrhWClEepHxOFP9/VwelsOM7r93fG7K/24JVfd7ItzSQPDxRje7bBoZ/P4aaUK53OCnde/nUn3H9LS9x8TROnsyIQCEIYn+Q1hzUeo6KiAvHx8SgvL0ejRu41lhPos6noZ5w4U4mBwq5DIBAIQh7a+VtopAQCSm5JFZoNgUAgEAQjjsQIBAKBQCAQmEQIUgKBQCAQCAQmEYKUQCAQCAQCgUmEICUQCAQCgUBgEiFICQQCgUAgEJhECFICgUAgEAgEJhGClEAgEAgEAoFJhCAlEAgEAoFAYBIhSAkEAoFAIBCYRAhSAoFAIBAIBCYRgpRAIBAIBAKBSYQgJRAIBAKBQGASIUgJBAKBQCAQmCTK6QyEOpIkAQAqKioczolAIBAIBAJa6ubtunlcDSFIceb06dMAgJSUFIdzIhAIBAKBwCinT59GfHy86u8+SU/UElji0qVLOHr0KBo2bAifz8c07oqKCqSkpODQoUNo1KgR07gFlxHlbA+inO1BlLM9iHK2B57lLEkSTp8+jeTkZEREqFtCCY0UZyIiItCiRQuuaTRq1Eh0VBsQ5WwPopztQZSzPYhytgde5ayliapDGJsLBAKBQCAQmEQIUgKBQCAQCAQmEYKUh4mNjcWzzz6L2NhYp7MS0ohytgdRzvYgytkeRDnbgxvKWRibCwQCgUAgEJhEaKQEAoFAIBAITCIEKYFAIBAIBAKTCEFKIBAIBAKBwCRCkBIIBAKBQCAwiRCkPMrcuXORmpqKuLg4pKenY926dU5nyTV88803uOuuu5CcnAyfz4ePP/446HdJkjBt2jQkJyejXr166NWrF3bs2BEUprKyEk888QQSEhLQoEEDDB06FIcPHw4Kc/LkSWRlZSE+Ph7x8fHIysrCqVOngsIcPHgQd911Fxo0aICEhAQ8+eSTqKqq4vHatjNjxgzcfPPNaNiwIZo1a4Zf/epX2L17d1AYUdbWefPNN3HjjTf6HQ5mZmbi888/9/8uypgPM2bMgM/nw4QJE/zfibK2zrRp0+Dz+YL+kpKS/L97sowlgedYsmSJFB0dLb3zzjvSzp07pfHjx0sNGjSQDhw44HTWXMGKFSukKVOmSMuWLZMASMuXLw/6/cUXX5QaNmwoLVu2TNq2bZs0cuRIqXnz5lJFRYU/zNixY6Wrr75ays3NlQoKCqTevXtLnTp1ki5evOgPc+edd0ppaWnShg0bpA0bNkhpaWnSkCFD/L9fvHhRSktLk3r37i0VFBRIubm5UnJysvT4449zLwM7GDBggPTee+9J27dvl7Zs2SINHjxYatmypXTmzBl/GFHW1vn000+lzz77TNq9e7e0e/duafLkyVJ0dLS0fft2SZJEGfNg06ZN0jXXXCPdeOON0vjx4/3fi7K2zrPPPivdcMMNUnFxsf+vtLTU/7sXy1gIUh7klltukcaOHRv0Xbt27aQ//elPDuXIvcgFqUuXLklJSUnSiy++6P/uwoULUnx8vDRv3jxJkiTp1KlTUnR0tLRkyRJ/mCNHjkgRERHSF198IUmSJO3cuVMCIH377bf+MHl5eRIAadeuXZIk1Qp0ERER0pEjR/xhPvzwQyk2NlYqLy/n8r5OUlpaKgGQ1q5dK0mSKGueNG7cWPr73/8uypgDp0+fltq2bSvl5uZKPXv29AtSoqzZ8Oyzz0qdOnUi/ubVMhZbex6jqqoK+fn56N+/f9D3/fv3x4YNGxzKlXcoKipCSUlJUPnFxsaiZ8+e/vLLz89HdXV1UJjk5GSkpaX5w+Tl5SE+Ph5du3b1h7n11lsRHx8fFCYtLQ3Jycn+MAMGDEBlZSXy8/O5vqcTlJeXAwCaNGkCQJQ1D2pqarBkyRKcPXsWmZmZoow58Pvf/x6DBw9G3759g74XZc2OPXv2IDk5Gampqbjvvvvw008/AfBuGYtLiz1GWVkZampqkJiYGPR9YmIiSkpKHMqVd6grI1L5HThwwB8mJiYGjRs3VoSpe76kpATNmjVTxN+sWbOgMPJ0GjdujJiYmJCrK0mSMGnSJNx+++1IS0sDIMqaJdu2bUNmZiYuXLiAK664AsuXL0eHDh38k4IoYzYsWbIEBQUF+O677xS/ifbMhq5du2LhwoW47rrrcOzYMTz//PPo1q0bduzY4dkyFoKUR/H5fEGfJUlSfCdQx0z5ycOQwpsJEwo8/vjj+P7777F+/XrFb6KsrXP99ddjy5YtOHXqFJYtW4ZHHnkEa9eu9f8uytg6hw4dwvjx47Fy5UrExcWphhNlbY2BAwf6/92xY0dkZmaiTZs2eP/993HrrbcC8F4Zi609j5GQkIDIyEiFxFxaWqqQrgVK6k6HaJVfUlISqqqqcPLkSc0wx44dU8R//PjxoDDydE6ePInq6uqQqqsnnngCn376Kb7++mu0aNHC/70oa3bExMTg2muvRUZGBmbMmIFOnTrhtddeE2XMkPz8fJSWliI9PR1RUVGIiorC2rVrMXv2bERFRfnfUZQ1Wxo0aICOHTtiz549nm3PQpDyGDExMUhPT0dubm7Q97m5uejWrZtDufIOqampSEpKCiq/qqoqrF271l9+6enpiI6ODgpTXFyM7du3+8NkZmaivLwcmzZt8ofZuHEjysvLg8Js374dxcXF/jArV65EbGws0tPTub6nHUiShMcffxwfffQRVq9ejdTU1KDfRVnzQ5IkVFZWijJmSJ8+fbBt2zZs2bLF/5eRkYEHH3wQW7ZsQevWrUVZc6CyshI//PADmjdv7t32bMg0XeAK6twfzJ8/X9q5c6c0YcIEqUGDBtL+/fudzporOH36tFRYWCgVFhZKAKRZs2ZJhYWFfvcQL774ohQfHy999NFH0rZt26T777+feLy2RYsW0qpVq6SCggLpjjvuIB6vvfHGG6W8vDwpLy9P6tixI/F4bZ8+faSCggJp1apVUosWLULiCLMkSdLvfvc7KT4+XlqzZk3QUeZz5875w4iytk52drb0zTffSEVFRdL3338vTZ48WYqIiJBWrlwpSZIoY54EntqTJFHWLHjqqaekNWvWSD/99JP07bffSkOGDJEaNmzon7+8WMZCkPIob7zxhtSqVSspJiZG6tKli//IuUCSvv76awmA4u+RRx6RJKn2iO2zzz4rJSUlSbGxsVKPHj2kbdu2BcVx/vx56fHHH5eaNGki1atXTxoyZIh08ODBoDAnTpyQHnzwQalhw4ZSw4YNpQcffFA6efJkUJgDBw5IgwcPlurVqyc1adJEevzxx6ULFy7wfH3bIJUxAOm9997zhxFlbZ1HH33U39evuuoqqU+fPn4hSpJEGfNELkiJsrZOnV+o6OhoKTk5WRo2bJi0Y8cO/+9eLGOfJEmSMR2WQCAQCAQCgQAQNlICgUAgEAgEphGClEAgEAgEAoFJhCAlEAgEAoFAYBIhSAkEAoFAIBCYRAhSAoFAIBAIBCYRgpRAIBAIBAKBSYQgJRAIBAKBQGASIUgJBAKBQCAQmEQIUgKBQCAQCAQmEYKUQCAQCAQCgUmEICUQCAQCgUBgEiFICQQCgUAgEJjk/wPY34EkIVmA3wAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<matplotlib.image.AxesImage at 0x7fc3f5b4f7f0>"
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ex_ind = 950\n",
    "ex = r_peaks_diffs[ex_ind]\n",
    "plt.plot(data_wide[ex_ind])\n",
    "plt.show()\n",
    "s = np.arange(1,128)\n",
    "#ex_normalized = normalize_1(ex)\n",
    "ex_cwt = calculate_cwt(ex, s)\n",
    "plt.imshow(ex_cwt, cmap='jet', aspect='auto',\n",
    "               vmax=abs(ex_cwt).max(), )\n",
    "plt.show()\n",
    "im = Image.fromarray(ex_cwt)\n",
    "\n",
    "plt.imshow(im, cmap='jet', aspect='auto',\n",
    "               vmax=abs(ex_cwt).max(), )\n",
    "plt.show()\n",
    "np_from_im = np.array(im)\n",
    "plt.imshow(np_from_im, cmap='jet', aspect='auto',\n",
    "               vmax=abs(ex_cwt).max(), )"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T16:14:46.665745334Z",
     "start_time": "2023-08-22T16:14:46.134467307Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "import csv\n",
    "def write_peaks_csv(peaks, stage):\n",
    "    with open('r_peaks/') as f:\n",
    "        for p in peaks:\n",
    "            f.write(str(item) for item in p )\n"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Could not save to PNG for display",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mKeyError\u001B[0m                                  Traceback (most recent call last)",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.9/site-packages/PIL/PngImagePlugin.py:1299\u001B[0m, in \u001B[0;36m_save\u001B[0;34m(im, fp, filename, chunk, save_all)\u001B[0m\n\u001B[1;32m   1298\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m-> 1299\u001B[0m     rawmode, mode \u001B[38;5;241m=\u001B[39m \u001B[43m_OUTMODES\u001B[49m\u001B[43m[\u001B[49m\u001B[43mmode\u001B[49m\u001B[43m]\u001B[49m\n\u001B[1;32m   1300\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mKeyError\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m e:\n",
      "\u001B[0;31mKeyError\u001B[0m: 'F'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001B[0;31mOSError\u001B[0m                                   Traceback (most recent call last)",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.9/site-packages/PIL/Image.py:681\u001B[0m, in \u001B[0;36mImage._repr_png_\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m    680\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m--> 681\u001B[0m     \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msave\u001B[49m\u001B[43m(\u001B[49m\u001B[43mb\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mPNG\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m)\u001B[49m\n\u001B[1;32m    682\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m e:\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.9/site-packages/PIL/Image.py:2431\u001B[0m, in \u001B[0;36mImage.save\u001B[0;34m(self, fp, format, **params)\u001B[0m\n\u001B[1;32m   2430\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m-> 2431\u001B[0m     \u001B[43msave_handler\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mfp\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mfilename\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m   2432\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m:\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.9/site-packages/PIL/PngImagePlugin.py:1302\u001B[0m, in \u001B[0;36m_save\u001B[0;34m(im, fp, filename, chunk, save_all)\u001B[0m\n\u001B[1;32m   1301\u001B[0m     msg \u001B[38;5;241m=\u001B[39m \u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mcannot write mode \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mmode\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m as PNG\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[0;32m-> 1302\u001B[0m     \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mOSError\u001B[39;00m(msg) \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01me\u001B[39;00m\n\u001B[1;32m   1304\u001B[0m \u001B[38;5;66;03m#\u001B[39;00m\n\u001B[1;32m   1305\u001B[0m \u001B[38;5;66;03m# write minimal PNG file\u001B[39;00m\n",
      "\u001B[0;31mOSError\u001B[0m: cannot write mode F as PNG",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001B[0;31mValueError\u001B[0m                                Traceback (most recent call last)",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.9/site-packages/IPython/core/formatters.py:344\u001B[0m, in \u001B[0;36mBaseFormatter.__call__\u001B[0;34m(self, obj)\u001B[0m\n\u001B[1;32m    342\u001B[0m     method \u001B[38;5;241m=\u001B[39m get_real_method(obj, \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mprint_method)\n\u001B[1;32m    343\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m method \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[0;32m--> 344\u001B[0m         \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mmethod\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m    345\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[1;32m    346\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.9/site-packages/PIL/Image.py:684\u001B[0m, in \u001B[0;36mImage._repr_png_\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m    682\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m e:\n\u001B[1;32m    683\u001B[0m     msg \u001B[38;5;241m=\u001B[39m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mCould not save to PNG for display\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[0;32m--> 684\u001B[0m     \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(msg) \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01me\u001B[39;00m\n\u001B[1;32m    685\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m b\u001B[38;5;241m.\u001B[39mgetvalue()\n",
      "\u001B[0;31mValueError\u001B[0m: Could not save to PNG for display"
     ]
    },
    {
     "data": {
      "text/plain": "<PIL.TiffImagePlugin.TiffImageFile image mode=F size=101x127>"
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#print(im.shape)\n",
    "im.save('delete.tiff')\n",
    "loaded_im = Image.open('delete.tiff')\n",
    "loaded_im\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T16:14:52.295627643Z",
     "start_time": "2023-08-22T16:14:52.114645964Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "outputs": [
    {
     "data": {
      "text/plain": "(128, 94)"
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images_5[100].shape"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T16:14:54.567133439Z",
     "start_time": "2023-08-22T16:14:54.550409616Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "outputs": [],
   "source": [
    "save_as_np(images_5, 5)\n",
    "save_as_np(images_2, 2)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T16:49:10.082312668Z",
     "start_time": "2023-08-22T16:49:06.676493855Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "outputs": [],
   "source": [
    "save_as_images(images_2, 2)\n",
    "save_as_images(images_5,5)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T16:18:58.722323188Z",
     "start_time": "2023-08-22T16:18:55.810809086Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "CWT From scaleogram i don't know how d_t should be when we have difference between peaks"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "outputs": [
    {
     "data": {
      "text/plain": "(128, 141)"
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# max_shape of the signal in this case\n",
    "max(images_5, key=lambda x: x.shape[1]).shape"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T14:50:08.827894685Z",
     "start_time": "2023-08-22T14:50:08.734570466Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tadeusz/miniconda3/envs/tf/lib/python3.9/site-packages/pywt/_functions.py:143: FutureWarning: Wavelets from the family cmor, without parameters specified in the name are deprecated. The name should takethe form cmorB-C where B and C are floats representing the bandwidth frequency and center frequency, respectively (example: cmor1.5-1.0).\n",
      "  wavelet = DiscreteContinuousWavelet(wavelet)\n",
      "/home/tadeusz/miniconda3/envs/tf/lib/python3.9/site-packages/scaleogram/wfun.py:173: FutureWarning: Wavelets from the family cmor, without parameters specified in the name are deprecated. The name should takethe form cmorB-C where B and C are floats representing the bandwidth frequency and center frequency, respectively (example: cmor1.5-1.0).\n",
      "  wavelet = pywt.DiscreteContinuousWavelet(wavelet)\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "Selected scale of 0.05555555555555555 too small.",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mValueError\u001B[0m                                Traceback (most recent call last)",
      "Cell \u001B[0;32mIn[90], line 8\u001B[0m\n\u001B[1;32m      6\u001B[0m fig, (ax1, ax2) \u001B[38;5;241m=\u001B[39m plt\u001B[38;5;241m.\u001B[39msubplots(\u001B[38;5;241m2\u001B[39m, \u001B[38;5;241m1\u001B[39m, figsize\u001B[38;5;241m=\u001B[39m(\u001B[38;5;241m14\u001B[39m, \u001B[38;5;241m6\u001B[39m))\n\u001B[1;32m      7\u001B[0m ax1\u001B[38;5;241m.\u001B[39mplot(time, ex)\n\u001B[0;32m----> 8\u001B[0m ax2 \u001B[38;5;241m=\u001B[39m \u001B[43mscg\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcws\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnp\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43marange\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mlen\u001B[39;49m\u001B[43m(\u001B[49m\u001B[43mex\u001B[49m\u001B[43m)\u001B[49m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\u001B[43mex\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mscales\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43ma\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mwavelet\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mwavelet\u001B[49m\u001B[43m,\u001B[49m\u001B[43myaxis\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mfrequency\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43mspectrum\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mpower\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m,\u001B[49m\n\u001B[1;32m      9\u001B[0m \u001B[43m \u001B[49m\u001B[43max\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43max2\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mcmap\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mjet\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mylabel\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mf [Hz]\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mxlabel\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mTime [seconds]\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\n\u001B[1;32m     10\u001B[0m \u001B[43m \u001B[49m\u001B[43myscale\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mlinear\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m)\u001B[49m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.9/site-packages/scaleogram/cws.py:138\u001B[0m, in \u001B[0;36mcws\u001B[0;34m(time, signal, scales, wavelet, periods, spectrum, coi, coikw, yaxis, cscale, cmap, clim, cbar, cbarlabel, cbarkw, xlim, ylim, yscale, xlabel, ylabel, title, figsize, ax)\u001B[0m\n\u001B[1;32m    136\u001B[0m     \u001B[38;5;66;03m# wavelet transform\u001B[39;00m\n\u001B[1;32m    137\u001B[0m     dt \u001B[38;5;241m=\u001B[39m time[\u001B[38;5;241m1\u001B[39m]\u001B[38;5;241m-\u001B[39mtime[\u001B[38;5;241m0\u001B[39m]\n\u001B[0;32m--> 138\u001B[0m     coefs, scales_freq \u001B[38;5;241m=\u001B[39m \u001B[43mCWT_FUN\u001B[49m\u001B[43m(\u001B[49m\u001B[43msignal\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mscales\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mwavelet\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mdt\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m    140\u001B[0m \u001B[38;5;66;03m# create plot area or use the one provided\u001B[39;00m\n\u001B[1;32m    141\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m ax \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.9/site-packages/scaleogram/wfun.py:232\u001B[0m, in \u001B[0;36mfastcwt\u001B[0;34m(data, scales, wavelet, sampling_period, method)\u001B[0m\n\u001B[1;32m    230\u001B[0m         out[i, :] \u001B[38;5;241m=\u001B[39m coef\n\u001B[1;32m    231\u001B[0m     \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m--> 232\u001B[0m         \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\n\u001B[1;32m    233\u001B[0m             \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mSelected scale of \u001B[39m\u001B[38;5;132;01m{}\u001B[39;00m\u001B[38;5;124m too small.\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;241m.\u001B[39mformat(scales[i]))\n\u001B[1;32m    234\u001B[0m frequencies \u001B[38;5;241m=\u001B[39m pywt\u001B[38;5;241m.\u001B[39mscale2frequency(wavelet, scales, precision)\n\u001B[1;32m    235\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m np\u001B[38;5;241m.\u001B[39misscalar(frequencies):\n",
      "\u001B[0;31mValueError\u001B[0m: Selected scale of 0.05555555555555555 too small."
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 1400x600 with 2 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import scaleogram as scg\n",
    "time = np.arange(len(ex))\n",
    "wavelet = 'cmor'\n",
    "d_t = 1\n",
    "a = pywt.central_frequency(wavelet) / (d_t * s)\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(14, 6))\n",
    "ax1.plot(time, ex)\n",
    "ax2 = scg.cws(np.arange(len(ex)),ex, scales=a, wavelet=wavelet,yaxis='frequency',spectrum='power',\n",
    " ax=ax2, cmap=\"jet\", ylabel=\"f [Hz]\", xlabel=\"Time [seconds]\",\n",
    " yscale='linear')\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-22T15:59:32.720458144Z",
     "start_time": "2023-08-22T15:59:32.322799242Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "import scipy.fftpack as fftpack\n",
    "N = len(ex)\n",
    "d_t  =1\n",
    "freqs = np.linspace(0,N/(2*d_t), N//2)\n",
    "fft=fftpack.fft(ex)\n",
    "fft_power = np.abs(fft[:N//2])**2\n",
    "plt.plot(freqs,fft_power)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-08-22T14:33:02.607327166Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "sus = data_wide[17006]\n",
    "plt.plot(sus)\n",
    "plt.plot(ex_cleaned)\n",
    "sus_peaks = neurokit2.ecg_peaks(ex_cleaned[:15000], sampling_rate=500)\n",
    "sus_peaks"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-08-22T14:33:02.607439197Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "noise = np.concatenate(data[17001:17026])\n",
    "plt.plot(noise)\n",
    "plt.plot(data[110])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-08-22T14:33:02.607547479Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "sus_peaks = neurokit2.ecg_peaks(ex_cleaned[:10000])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-08-22T14:33:02.607621750Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "def plot_with_peaks(y, r_peaks, detector_name='nodetect', sampling_freq=500):\n",
    "    # convert sample to nr to time\n",
    "    r_ts = np.array(r_peaks) / sampling_freq\n",
    "    # plotting\n",
    "    plt.figure()\n",
    "    t = np.linspace(0, len(y) / sampling_freq, len(y))\n",
    "    plt.plot(t, y)\n",
    "    plt.plot(r_ts, y[r_peaks], 'ro')\n",
    "    plt.title(f\"{detector_name}\")\n",
    "    plt.ylabel(\"ECG/mV\")\n",
    "    plt.xlabel(\"time/sec\")\n",
    "    plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-08-22T14:33:02.607748311Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "ex_data = data_wide[100]\n",
    "ex = neurokit2.ecg_peaks(ex_data, sampling_rate=500)[1]['ECG_R_Peaks']\n",
    "plot_with_peaks(ex_data, ex)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-08-22T14:33:02.607828912Z"
    }
   }
  }
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